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New today · July 27, 2026
What the posting requires: - 0 to 1 years in software development, ideally with internships in integrations or data tools. This is the stated candidate persona and it is the reason this role is on the list. - A B.Tech in Computer Science or equivalent from a reputed college. This is stated in the posting. - Basic object oriented programming skills and familiarity with design principles. - Exposure to data pipelines or APIs, and eagerness to learn concurrency and performance basics. - Foundational knowledge of REST APIs, for example making calls and handling JSON. The posting says explicitly that no deep expertise is needed here. - Proficiency in Java, TypeScript or Python, with good problem solving using data structures and algorithms. - Strong analytical and logical thinking for real world challenges. What the work actually looks like: - Implement SaaS connectors for assigned applications, learning application specific nuances such as basic auth and data extraction. - Assist in building simple REST API components, focusing on clean implementation and testing. - Debug and optimise code for data pipeline efficiency, under mentorship. - Contribute to feature breakdown, coding and documentation for smaller tasks. - Apply logical thinking to solve integration issues and improve component quality. What this tells you about the role: the words under mentorship and assist appear in the responsibilities, which is a good sign for a first job. You are not being asked to own a system alone. The work is connector and integration engineering, which is a real specialism and a useful one, since almost every SaaS company needs people who can make two systems talk to each other. About the company: Hevo is based in San Francisco and Bangalore, powers data analytics for more than 2,000 companies across 45 plus countries, and states its mission as building technology from India for the world that is simple enough that anyone can unlock the potential of their data. Location and working pattern: Bengaluru. Office days are not stated. Honest fit guidance: if you are a recent graduate or in your first year, this is the role on today's list to spend your best application on. The degree requirement from a reputed college is stated explicitly, so know that going in if your background is non traditional. Prepare by being able to talk about an API you have consumed and a data problem you have debugged, because that is exactly what the responsibilities describe. No interview process is published.
What the posting requires: - A Bachelor's or Master's in Computer Science, Engineering or a related field, with 5+ years of enterprise integration experience. - At least 3 years of integration development using platforms such as Workato, MuleSoft or Boomi. - Deep understanding of enterprise integration design patterns, messaging and event driven architectures, plus Workato concepts including callable recipes, event streams and task optimisation. - Proficiency with Workato connectors including Salesforce, NetSuite, HRIS and Google Workspace, along with Python or Ruby scripting. - Strong development experience implementing Workato at scale: automation, observability and monitoring, and debugging in complex environments with many connected systems, plus DevOps process adhering to compliance, audit and internal CI/CD. - Hands on experience implementing secure and scalable REST APIs, and implementing Workato MCP and agentic workflows. - Strong problem solving and debugging across multiple connected systems and their environments. - Excellent analysis and design ability, with focus on system design, flow, scalability and performance, and mapping business requirements to technical solutions. What the work actually looks like: - Automate, develop and support integrations across various business systems, platforms and tools. - Work with different business units and technical teams to gather requirements and design solutions. - Create scalable solutions and operationalise integrations. - Implement and promote integration best practices. - Participate in an on call support rotation. The success measures the employer publishes: - Deliver high quality, scalable integration recipes and flows within the Quote to Cash process and other GTMTech programmes, on time. - Successfully deploy and operationalise integrations while keeping system stability and performance. - Proactively identify and resolve complex integration issues with minimal disruption to core business operations. - Translate complex requirements into technical design with business and technical teams. Location and working pattern: the posting states MongoDB wants candidates based in Gurugram for its hybrid working model. Honest fit guidance: the Workato requirement is specific and enforced, so this suits an integration specialist rather than a general backend engineer. If you have built on MuleSoft or Boomi the transferability is real. The on call rotation is stated, so factor it in.
What the posting requires: - 5+ years of experience in analytics or data science, with a strong track record of solving ambiguous business problems. - Functional expertise building analytical solutions, and the ability to be a trusted partner to business teams and leaders through insights and recommendations. What the work actually looks like: - Build agentic analytics pipelines that automate insight generation across key metrics including contact volume, handle time and resolution quality. - Develop reusable skill libraries: composable agent tools such as volume lookups, NPS pulls and handle time calculations, callable across workflows and teams. - Design and govern prompt templates and playbooks: standardised, governed prompts for recurring analytical questions, for example what drove contact volume this week. - Build orchestration workflows: multi step pipelines that chain skills together to produce automated insight narratives and proactive alerts without manual intervention. - Deploy self serve interfaces that let non technical people query certified data independently. - Ship rapid, prompt driven dashboards that compress the cycle from business question to live view. - Automate business reviews with scheduled, agent generated summaries of key metrics. - Build and maintain evaluation and observability frameworks for those systems. Who you would work with: business and operational leaders across Airbnb's Community Support organisation, sitting under the Advanced Analytics family within the Analytics Centre of Excellence. What the team does more broadly: the ACOE delivers metrics, dashboards, performance optimisation, pre and post feature impact measurement, opportunity sizing, anomaly driven alerting, root cause analysis of metric deviation and exploratory hypothesis testing. Location and working pattern: Gurugram, India. This is the Gurugram based role, not a remote one. Honest fit guidance: read the AI framing as real rather than decorative. The responsibilities are almost entirely about building agentic tooling and self serve interfaces, not producing analyses by hand. If your analytics experience is SQL and dashboards with no agent or LLM tooling, that is the honest gap. If you have been building with agents and want an analytics seat where that is the job rather than a side project, this is a strong match at 5 years.
What the posting requires: - A Bachelor's degree in Computer Science, Engineering or a related field. - 5+ years of professional Java development experience with Spring, JDBC, and MyBatis or Hibernate or equivalent. - Experience with application modernisation, database migrations or large scale refactoring initiatives. - Strong SQL expertise: you can analyse, interpret, optimise and rewrite complex SQL embedded in Java applications. - Deep understanding of JDBC, ORMs, Java transaction patterns and database driven application flows. - Experience on enterprise grade, high performance applications with complex data interactions. - Strong communication skills and the ability to work with globally distributed teams in US time zones. Nice to have: - Experience with PostgreSQL or Aurora PostgreSQL, or modernisation from legacy databases such as Oracle, SQL Server or DB2. - Exposure to automated code refactoring tools or GenAI assisted remediation workflows. - Familiarity with CI/CD environments, performance testing tools and observability stacks. - Consulting or professional services experience delivering fixed timeline modernisation projects. What the work actually looks like: - Analyse and remediate large enterprise Java codebases, replacing legacy and database specific SQL constructs with modern, standards compliant SQL. - Convert embedded SQL in Java services and MyBatis XML mappers: vendor specific functions, sequences, pagination logic, dynamic SQL and error handling patterns. - Work with schema and database migration engineers so application layer SQL lands aligned with the modernised target schema. - Refactor Java transaction logic, error handling, drivers and ORM or DAO layers. - Run unit, integration and performance testing to confirm functional parity and hit performance SLAs after modernisation. - Support production cutover: validation, monitoring setup, rollback planning and stabilisation until the system holds. - Produce engineering documentation that outlives the engagement: SQL remediation guides, code migration runbooks, troubleshooting guides and knowledge transfer material. What the company says about how the work splits: the agent platform does the repetitive 60 to 70 percent that a traditional consulting engagement would staff humans for, including mechanical SQL conversion and the regression harness. Your hours go to the refactoring judgement. Location and working pattern: Mumbai, with distributed collaboration across US and India teams and an expectation of overlap with US time zones. Honest fit guidance: this is deep, unglamorous, high value work. If you have lived inside a large Java codebase with vendor specific SQL, five years is enough. If your Java is greenfield microservices only, the legacy remediation requirement is the gap.
What the posting requires as mandatory: - Experience of 5 to 8 years for the Staff level, or 9 to 12 years for the Sr Staff level. One posting, two levels, so read the band that matches you. - Strong programming experience in Java. - Strong computer science fundamentals, especially algorithms, data structures, object oriented programming and SQL. - Hands on experience with Spring and Spring Boot, and ORM frameworks. - Good understanding of database internals and schema design across different data stores, both relational and NoSQL. - Experience designing and developing APIs for large scale data systems with low latency. - Experience working in a client server, cloud hosted environment. - Strong analytical and problem solving skills. Good to have: - Experience with AWS, described as highly desirable. What the work actually looks like: Device health and monitoring: - Understand IoT devices and accessories to build and enhance device monitoring and health solutions. - Develop systems for device health monitoring covering camera, LTE, GPS, storage, power, real time clock and accessories. - Implement device online and offline detection and recovery mechanisms. - Design health state transitions and root cause classification for device issues. Backend and platform: - Design, develop and maintain high performance, reliable, reusable backend services. - Build and test large scale SaaS products processing massive volumes of real time data. - Build and operate systems processing hundreds of millions of IoT sensor events per day. System design and ownership: - Translate product requirements into technical designs and tasks, and execute across the full development lifecycle. - Design APIs with low response times and efficient resource use for large data sets. - Provide technical guidance and mentorship to junior engineers, and debug complex issues to root cause. ⚠️ Location and working pattern, stated explicitly: Whitefield, Bangalore, **on site 5 days a week**, general shift or evening shift. Netradyne is one of the few employers on this board that publishes its office policy, and this one is fully in office with a possible evening shift. Factor that in before applying. A note on the employer: Netradyne postings carry a recruitment fraud warning. Official communication comes only from netradyne.com or us-greenhouse-mail.io addresses, and the company never charges candidates a fee. Honest fit guidance: if you have 5 to 8 years of Java backend work at scale, apply to the Staff band rather than being put off by Sr Staff in the title. IoT domain experience is not required, but comfort with high volume event processing is.
What the posting requires: - 5 to 10 years of experience in field engineering, enterprise deployment or senior IT support roles. - Deep, hands on expertise with Intune and SCCM covering policy design, compliance management and large scale fleet deployment. The posting marks this **non negotiable**. - Advanced PC hardware diagnostics across BIOS, firmware and hardware level troubleshooting on varied enterprise device configurations. Also marked **non negotiable**. - Strong PowerShell scripting, with the ability to build and maintain automation frameworks for enterprise environments. - Expert level knowledge of Windows OS in enterprise and managed fleet contexts. - A proven track record in customer facing technical roles, comfortable engaging enterprise IT leadership. - Experience owning SLA management and escalation governance across multiple enterprise accounts. Bonus points: - Prior experience with on device AI, edge computing or sovereign enterprise AI deployments. What the work actually looks like: - Lead deployment and configuration of Sarvam's on device AI platform across large enterprise PC fleets using Intune and SCCM. - Own escalated hardware diagnostics, resolving complex BIOS, firmware, driver and hardware level issues. - Architect and maintain PowerShell automation frameworks for deployment, monitoring and configuration management at scale. - Define and enforce MDM policy architecture via Microsoft Intune. - Drive presales engagements: technical discovery, scoping proof of concept deployments, and presenting to enterprise IT leadership. - Own SLA governance across a portfolio of enterprise accounts, managing escalations and resolution quality. - Act as primary technical liaison between enterprise customers and Sarvam's product and engineering teams. - Build and maintain deployment playbooks, technical runbooks and support documentation. - Mentor and guide other field engineers. What makes the context unusual: the posting describes the team as co owning the most ambitious on device AI problem in India, building sovereign models that run at the silicon level, embedded with partners including Qualcomm, Intel, HP, Apple and NVIDIA. Location and working pattern: Bengaluru, described as on site or hybrid, with significant customer facing and mentoring responsibility. Honest fit guidance: this is enterprise endpoint engineering more than it is AI engineering, and the two non negotiables tell you where applications will be judged. If your background is Windows fleet management at scale and you want to work at an AI company, it is a rare bridge. If you want to build models, this is not that role.
What the posting requires: - 5 to 8 years in field engineering, solutions engineering, technical account management or senior client facing engineering roles. - Strong Python proficiency, with the ability to read, debug and contribute to production FastAPI services and ML pipelines. Marked **non negotiable**. - Experience with audio and video processing workflows: FFmpeg, codec pipelines, media formats or streaming infrastructure. Also marked **non negotiable**. - A proven track record working with enterprise media, OTT or content localisation clients. - Comfort operating across the stack: REST APIs, async job queues such as Celery or Redis, PostgreSQL, cloud storage on Azure, GCP or AWS, and Kubernetes. - Strong debugging instincts, tracing failures across distributed systems from API through queue and worker to ML inference and storage. - Experience owning SLA management and escalation governance across multiple enterprise accounts. - Excellent communication, comfortable engaging CXO and VP level stakeholders. What the work actually looks like: - Lead end to end integration of the dubbing platform into enterprise content workflows across OTT, media houses, ed-tech and enterprise learning and development. - Own the technical relationship with strategic accounts: scoping requirements, designing integration architecture and ensuring production readiness. - Debug and resolve complex pipeline issues across the full dubbing stack: audio separation, speech recognition, translation, text to speech and video stitching. - Tune pipeline parameters for client specific content: voice activity detection thresholds, translation glossaries, TTS voice profiles and audio mixing. - Drive presales engagements including technical discovery and proof of concept scoping. - Build and maintain integration playbooks, API guides and troubleshooting runbooks. - Define SLA governance across enterprise accounts covering turnaround time, quality benchmarks and escalation resolution. - Act as primary technical liaison between enterprise clients and Sarvam's dubbing product and ML engineering teams. - Mentor other field engineers, and contribute fixes back to internal platform codebases when client deployments surface bugs. Location and working pattern: Bengaluru, with significant customer facing responsibility. Honest fit guidance: the media pipeline experience is the differentiator. Plenty of engineers can debug a distributed system, far fewer have worked with FFmpeg and codec pipelines, and that is what the posting marks non negotiable alongside Python. If you have both, the customer facing element is learnable. If you have neither, the title being FDSE will not carry the application.
What the posting requires: - 6 to 9 years of software development experience with enterprise grade software. - Experience building scalable, high performance cloud services. - Expert coding skills in Scala or Java backend. The product is built in Scala on the Lightbend stack with Play and Akka. - Deep knowledge of databases, query optimisation and views. - Development on cloud platforms including AWS. - Expertise building scalable, event based asynchronous systems on a microservices architecture. - Experience with Docker and Kubernetes. - Expertise building REST APIs. - Cybersecurity experience and adversarial thinking. - Willingness to learn, challenge yourself and share ideas with the team. - Ability to multitask across roles in a fast paced environment: leading a feature design one week, fixing a critical bug or improving CI the next. - A BSCS or equivalent is required, MSCS or equivalent strongly preferred. What the work actually looks like: - Work with the engineering team to design, build and test the cloud based platform across front end, back end and services. - Participate in feature estimation and prioritisation, sprint planning, biweekly sprints, code reviews and retrospectives. - Contribute to product development: understand customer needs and work with product to design, plan and implement new features. - Support early customers by investigating and fixing production issues. - Improve processes and make the right tradeoffs between agility, cost and reliability. Levelling, which matters here: the posting states this team is hiring across all levels and that candidates are individually assessed and levelled based on their skills and experience. So the Staff in the title is not a hard floor. Location and working pattern: listed as India without a specific city. Netskope has a Bangalore office and describes open desk layouts, so confirm the base location with the recruiter. Honest fit guidance: the Scala requirement is the real filter. Netskope will take strong Java backend engineers, since the posting says Scala or Java, but the codebase is Scala on Play and Akka and you would be working in it daily. If you have wanted an excuse to work in Scala at scale on a security product, this is one of the few such roles in India. The early team member framing means less structure than a mature team.
What the posting states: - Experience required: 6 to 9 years. - Native Android and iOS development. The title specifies both platforms rather than one, so cross platform depth is the expectation rather than a single specialism. - Employment type: full time. What the work involves, based on the role and the product: building and maintaining the native mobile applications through which fleet customers and drivers interact with Netradyne's driver monitoring and safety scoring platform, working alongside the backend, embedded and analytics teams that produce the data those apps display. ⚠️ Location and working pattern, stated explicitly in the posting: Whitefield, Bangalore, **on site 5 days a week**, general shift or evening shift. This is one of the few postings on today's board that publishes its office policy precisely. If you need hybrid or remote, this role is not it, and the evening shift possibility is worth clarifying at first contact. About the employer: Netradyne provides AI powered technologies for fleet management and road safety, is an award winning leader in fleet safety and video telematics, and serves thousands of commercial fleet customers across North America, Europe and Asia. Founded in 2015, headquartered in San Diego with offices in San Francisco, Nashville, the UK and Bangalore. The company reports growth exceeding 4x year over year. A note on the employer: Netradyne postings carry a recruitment fraud warning. Official communication comes only from addresses ending in netradyne.com or us-greenhouse-mail.io, the company never requests sensitive personal data over text or unsecured channels, never promises advance payment for work equipment, and never uses agencies that charge candidates a fee. Honest fit guidance: this posting is thinner on detail than most on today's list, so treat the 6 to 9 years and the dual platform requirement as the firm parts and ask the recruiter about scope, team size and what the apps actually do. The office policy is the clearest signal in it and it is a strict one. If you are a native mobile engineer in Bangalore who is fine with full time office work, the product is more interesting than most: real vehicles, real safety outcomes, real scale.
What the posting states: - Job title: Staff Engineer, Embedded System Engineer. - Department: Device. - Experience: 6 to 12 years. That is a wide band in a single posting, so treat 6 as the real floor. What the work involves, based on the department and product: embedded software for Netradyne's edge devices, the camera units that run computer vision on the vehicle itself rather than in the cloud. That work sits alongside the company's other device roles covering multimedia pipelines, middleware on Linux, board support package development and hardware engineering, all of which Netradyne staffs separately, so expect a specialised slice rather than the whole device stack. Location and working pattern: Bangalore. This particular posting does not state the number of office days, though several other Netradyne listings specify on site five days a week at Whitefield. Ask rather than assume, because the company's other device roles are explicitly full time in office. About the employer: Netradyne provides AI powered technologies for fleet management and safer roads, is an award winning industry leader in fleet safety and video telematics, and empowers thousands of commercial fleet customers across North America, Europe and Asia. It sets its standard on 25 plus billion miles vision analysed for risk and an industry first driver scoring system. Founded in 2015, headquartered in San Diego with offices in San Francisco, Nashville, the UK and Bangalore. A note on the employer: Netradyne includes a recruitment fraud warning in its postings. Official communication comes only from netradyne.com or us-greenhouse-mail.io addresses, the company does not request sensitive personal data via text or unsecured channels, does not promise advance payment for equipment setup, and does not use agencies that charge candidates a fee. Honest fit guidance: this posting is light on a requirements list, which cuts both ways. It means fewer boxes to fail on, and it means you should ask early which part of the device stack the role covers, since Netradyne runs separate reqs for multimedia, middleware, BSP and hardware. If you have shipped embedded software on Linux based devices and want work where the constraint is real hardware rather than cloud cost, six years is enough to be taken seriously here.
What the posting requires as minimum qualifications: - A minimum of 6+ years of experience in technical support, with at least 4 years focused on DLP and CASB solutions. - A foundational understanding of AI and ML technologies, and experience leveraging, securing or positioning AI driven solutions within your functional domain. Zscaler lists this first. - Experience with data loss prevention, securing SaaS, and Cloud Access Security Brokers. - Practical working knowledge of AWS, Azure or GCP cloud environments, paired with a strong understanding of Unix, Linux and Windows operating systems. - Deep understanding of data protection principles and practices. Preferred qualifications: - Experience deploying or supporting AI powered sensitive data discovery tools or automated data classification models to enhance DLP capabilities. - Experience with scripting and automation using Python or PowerShell. - Knowledge of regulatory requirements and compliance standards such as GDPR, HIPAA or PCI DSS. What the work actually looks like: - Provide advanced troubleshooting and resolution for complex DLP issues raised by enterprise customers. - Perform root cause analysis to identify underlying problems and implement lasting solutions. - Work with product development, engineering and other cross functional teams to resolve issues and improve Zscaler's DLP products. - Maintain clear and proactive customer communication through the support process. How this compares to the neighbouring role: Zscaler also lists an Escalation Engineer DLP requiring 8+ years with at least 5 on DLP. Same specialism, one level up. If you sit between 6 and 8 years this posting is the better fit, and the escalation one is a natural next step. Location and working pattern: Bangalore or Mohali. Zscaler's DLP postings are described as hybrid roles based in those offices, reporting into Product Support. What Zscaler says about its culture: impact over activity, constructive and honest debate, customer obsession, ownership and accountability, with an emphasis on using AI to amplify individual impact. Honest fit guidance: the 4 years specifically on DLP and CASB is the filter, not the 6 years overall. General cloud support experience will not clear it. Support engineering at this tier is genuinely technical work with direct engineering contact, but be clear eyed that it is a support function with the customer communication load that implies.
What the posting requires: - A BS or higher in Computer Science, or a related field. - 7+ years of production level experience in one of Java, Scala, C++ or a similar language. - Comfort working towards ambitious goals in a fast moving environment. - Experience developing large scale distributed systems. - Hands on experience developing and operating backend systems. What the work actually looks like, given the team's remit: - Build and operate the platform systems behind usage metering, billing and revenue for Databricks. - Solve real business needs at large scale through software engineering. - Contribute across project phases from design and development through implementation and ongoing operations. - Investigate and help prevent production issues, since correctness in this domain is directly customer visible. Why this kind of team is worth considering: money and billing systems are usually the highest correctness bar in a company. The data volumes are the same as the rest of the platform, but the tolerance for error is far lower, which tends to mean strong engineering practice, good testing culture and clear ownership. Location and working pattern: Bengaluru. Databricks says it is in the process of setting up new teams from scratch at this site, so expect an in office or hybrid arrangement. The exact number of days is not stated in the posting. Compliance note in the posting: where a role requires access to export controlled technology or source code, Databricks states that applying for a US government licence is at its discretion, and it may decline to proceed with an applicant on that basis alone. Worth reading before investing time in the process. Honest fit guidance: seven years of real production backend work is the bar, and the language list is broad enough that the specific language matters less than the scale you have operated at. If you have worked on billing, metering, payments or any system where a wrong number is a customer incident, say so prominently in your application, because that is exactly the experience this team is buying.
What the posting requires: - 7+ years of experience in information security, with at least 5 years focused specifically on endpoint security engineering. - Deep hands on expertise with enterprise EDR platforms. The posting names CrowdStrike Falcon, Microsoft Defender for Endpoint, SentinelOne and Carbon Black. - Strong experience deploying, managing and tuning enterprise DLP solutions. Named examples are Microsoft Purview, Symantec DLP and Cyberhaven. - Demonstrated experience in insider threat detection and response, including familiarity with UEBA tools and behavioural analytics. Nice to have: - Experience with hybrid cloud environments across AWS, Azure and GCP. - Prior experience in the EV, automotive or critical infrastructure industry. What the work actually looks like: - Lead insider threat detection and response: build and maintain detection logic, investigate anomalous user behaviour, and drive incident response for insider threat cases. - Manage and mature the enterprise data loss prevention programme: define and refine DLP policies, monitor alerts, investigate violations and coordinate remediation with stakeholders. - Own end to end management of the enterprise EDR platform across Windows, macOS and Linux endpoints, covering deployment, policy configuration, tuning and ongoing optimisation. ⭐ Location and working pattern: the posting states **Gurgaon or remote**. That makes this the only role on today's board with a remote option, which matters if relocation is what stands between you and a job. The posting does not elaborate on what remote means in practice, so confirm the expectation, including any travel or occasional office days, before assuming it is fully remote. About the employer: ChargePoint has focused since 2007 on making the transition to electric easy for businesses, fleets and drivers, and operates hardware, software and mobile solutions across North America and Europe. Honest fit guidance: the 5 years specifically on endpoint security is the real filter rather than the 7 years overall. This is corporate security engineering, so if you want product security or application security work this is a different discipline. ChargePoint states it provides reasonable accommodations throughout the hiring process and publishes an email address for accommodation requests.
What the posting requires: - 7 to 10 years of experience in FP&A systems, enterprise performance management or enterprise planning implementations. - Hands on experience in at least one platform: Pigment (preferred), Anaplan, or Workday Adaptive Planning. - Strong understanding of financial planning processes and financial statements, annual sales planning, and driver based modelling and forecasting. - Experience with ERP systems, NetSuite preferred. - Experience with CRM systems, Salesforce preferred. - Experience with data warehouses. Additional technical skills: - Exposure to Python or scripting is described as a plus. - Experience with ETL and integration tools. Preferred qualifications: - Certifications: Anaplan Certified Model Builder or Solution Architect, Workday Adaptive Planning certification, or Pigment Modeler experience. - Experience supporting SaaS or consumption based business models. - Exposure to headcount and compensation planning, annual sales planning, and revenue modelling covering ARR, churn and expansion. - Experience working in a Global Capability Centre or offshore delivery model. What the work actually looks like: Enterprise planning delivery: - Design and build scalable planning models across financial planning (profit and loss, cash flow, balance sheet), workforce planning and cost modelling, and sales and revenue forecasting (ARR, pipeline, bookings). - Own end to end delivery working with the product manager: design, build, test, deploy and support. Model development and optimisation: - Build multi dimensional, driver based models with a strong focus on performance. - Develop scenario planning, versioning and forecasting capabilities. - Optimise model size and calculation performance. Location and working pattern: the posting states MongoDB is looking for candidates based in Bengaluru or Gurugram for its hybrid working model. Honest fit guidance: be clear with yourself about what this is. It is a specialist enterprise planning platform role, closer to FP&A systems work than to backend software engineering, and the certifications listed under preferred qualifications tell you the discipline it belongs to. If you have built models in Anaplan, Pigment or Adaptive Planning, this is a strong senior seat at a well known technology company. If you are a software engineer hoping this is a finance flavoured coding job, it is not.
What the posting requires as mandatory: - A B.Tech, M.Tech or PhD in Computer Science, Electrical Engineering, Statistics, Mathematics or a related field. - 8+ years of experience in data science, analytics or a closely related domain. - Strong foundation in probability, statistics and estimation theory. - Strong programming in Python, with solid fundamentals in object oriented programming, algorithms and data structures. - Deep familiarity with SQL, complex query writing, indexing and database internals, plus working knowledge of at least one NoSQL store. - Experience with data visualisation and analytical storytelling. - Excellent written and verbal communication. - Familiarity with AI powered tools for analytics and software development, including using them for exploratory analysis, experiment analysis and documentation, and critically evaluating AI generated output for correctness, statistical validity and reproducibility. Preferred skills: - Exposure to cloud platforms and services such as AWS Kinesis, EKS and autoscaling systems. - Experience building lightweight web or service components with Flask or Django. - Prior experience with large scale, noisy, real world datasets. What the work actually looks like: - Design, implement and maintain offline and online evaluation frameworks for AI and ML features. - Define, validate and evolve the KPIs, success metrics and audit methodologies used across teams. - Perform deep error analysis, bias analysis and segmentation to identify failure modes. - Own golden datasets, validation protocols and benchmarking standards. - Conduct large scale analytical studies on feature performance, data quality and system behaviour. - Design and review experiments including offline evaluations, controlled rollouts and A/B tests, ensuring statistical correctness. - Perform post deployment monitoring and regression detection. - Build tools, dashboards and automation to scale audits and reporting. - Mentor junior data scientists on statistical rigour, experiment design and analytical storytelling. How this differs from the 5+ years version of this role published on this board on 2026-07-26: same team and same responsibilities, but this posting sets the bar at 8+ years rather than 5+. If you are between 5 and 8, look for the other one. Location and working pattern: Bangalore. This posting does not state office days, though other Netradyne listings specify five days on site. Honest fit guidance: if you want to build models, this is explicitly not that role. It suits someone happier proving whether a system works than building it, and willing to tell a product team its metric is wrong.
What the posting requires: - 8+ years of production level experience in one of Python, Java, Scala, C++ or a similar language. - 4+ years of experience in a networking focused context, which is the specialism this role is hiring for. - Experience developing large scale distributed systems. - Hands on experience developing and operating backend systems. What the work actually looks like, given the team's remit: - Build and operate the networking layer for a platform running across AWS, Azure and GCP at a fleet size measured in millions of virtual machines. - Handle the differences between cloud providers' networking primitives, and design so that provider level faults degrade gracefully rather than breaking customer workloads. - Low level systems debugging and performance measurement on large production clusters. - Contribute across the project lifecycle from design through implementation and ongoing operation. The operating context Databricks describes: at its scale the company routinely observes cloud hardware, network and operating system faults, and the software is expected to shield customers from all of them. That is the daily reality of a networking role there rather than an abstract claim. Location and working pattern: Bengaluru. Databricks says it is standing up new teams from scratch at this site, so expect an in office or hybrid arrangement, with the number of days not stated. Compliance note in the posting: the standard Databricks export controlled technology clause applies. Where such access is required, applying for a US government licence is at the employer's discretion and it may decline to proceed on that basis. Honest fit guidance: the 4 years of networking experience is what separates applications here, not the 8 years overall. Cloud networking at multi provider scale is a narrow skill and the people who have it are usually not looking, which is a reason to apply if you do. If your networking exposure is configuring a VPC occasionally, the requirement is deeper than that.
What the posting requires: - 8+ years of experience building distributed systems and/or foundational cloud services at scale, with an interest in working with Python, Go and Java. - A strong background building core components for high scale compute and data distributed systems. - Proven success in designing, writing, testing, debugging and performance tuning, with a strong grip on computer science fundamentals, and maintaining distributed or highly concurrent software in large, long lived codebases. - A track record of identifying problems and implementing solutions. - Eagerness to learn, with a strong technical background. - The ability to be a force multiplier in the software development process, enabling teams to deliver through leadership and technical contribution. Bonus points: - Experience with containerisation and orchestration platforms such as Kubernetes. - Experience with AI frameworks and tools. What the posting sets as position expectations: - Work closely with research, product management, product engineering, product design and other teams to define the first version and future evolution of the service. - Design, build and deliver well tested core pieces of the platform in collaboration with other stakeholders. - Contribute to shaping architecture, code reviews, development practices and developer experience as the teams and product grow. - Mentor fellow engineers and assume ownership and accountability of projects. What kind of role this is: defining the first version of a service means less existing structure and more influence over how it is built. That is attractive if you want architectural ownership and frustrating if you prefer a mature codebase with settled patterns. Location and working pattern: the posting states MongoDB is looking for candidates based in Gurugram for its hybrid working model. Honest fit guidance: eight years is a real bar here because the role is about judgement as much as output. The distinguishing experience is having maintained distributed systems in large, long lived codebases, which is different from having built greenfield services that never had to survive five years. If you have both, say so.
What the posting requires: - 8+ years of software engineering experience, described as being a master of fundamentals. This is the E4 level; Instawork also lists an E3 version of the same role at 6+ years. - Full stack versatility: able to move between frontend, backend and infrastructure and own features end to end. - Comfort designing user experience in React and diving into AWS to tune heavy video transcoding pipelines. - Ability to architect and scale cloud environments, including complex AWS infrastructure and ECS services. - Deep observability practice with precise telemetry across CPU, memory, network and disk IOPS. - Ability to design and optimise data pipelines at scale. - Strong engineering intuition and architectural expertise. The team leverages agentic coding models heavily and says it relies on human judgement to keep systems robust and built the right way. What the work actually looks like: - Own the technical execution for massive scale physical AI training data. - Lead technical development of the global data collection platform and the dedicated quality assurance platform, ensuring high throughput data enrichment, labelling and continuous quality assurance loops. - Architect and scale cloud environments, managing AWS infrastructure and ECS services for video transcoding. - Design and optimise data pipelines capable of operating at scale. - Act as a key engineering leader in the Bengaluru hub. What the business actually does, since it is unusual: Instawork Robotics Labs deploys skilled hourly workers into real commercial and residential environments to capture task data, which robotics labs then use to train foundation models. The posting frames closing that data gap as the defining infrastructure challenge of the physical AI era. Location and working pattern: Bengaluru. Office days are not stated. Honest fit guidance: the posting asks for a generalist and means it, so specialists who have worked in one layer will struggle against the breadth requirement. Video pipeline and transcoding experience is the part most candidates lack. If you are between 6 and 8 years, apply to the E3 posting instead of stretching for this one, since both are open.
What the posting requires as minimum qualifications: - A foundational understanding of AI and ML technologies, and experience leveraging, securing or positioning AI driven solutions to optimise outcomes within your functional domain. Zscaler lists this first. - 8+ years of support and networking experience as a subject matter expert specialising primarily in Zscaler Client Connector technologies. - Expertise in networking, cloud security and performance management, with the ability to quickly master new technologies. - Proven effectiveness at collaborating and building consensus across cross functional teams and organisations. - Experience developing new processes, tools or product features. What the work actually looks like: - Act as the deep subject matter expert on client connector technology for the wider support and engineering organisation. - Develop new processes, tools and product feature input rather than only resolving individual cases, which is what distinguishes a Center of Excellence seat from escalation work. - Collaborate across support, engineering and product to drive consistent outcomes. What Zscaler says about the environment: an AI forward enterprise built around the world's largest security data lake powering its cloud native Zero Trust Exchange platform. Culturally it emphasises impact over activity, constructive and honest debate, customer obsession, ownership and accountability, and a bias toward speed with quality. Location and working pattern: Bangalore or Mohali. Zscaler's support organisation roles in these locations are generally hybrid, though this particular posting does not spell the arrangement out, so confirm it. Honest fit guidance: the specialism is narrow and named. If you have spent years on Zscaler Client Connector or a directly comparable endpoint agent in a security platform, that specific depth is what is being bought and the 8 years is a fair reflection of it. If your background is general network support without that agent level depth, the requirement is more specific than it first appears. The process and tooling development part of the role is worth weighing positively: it is what makes this more than a support ladder step.
What the posting requires as minimum qualifications: - A foundational understanding of AI and ML technologies, and experience leveraging, securing or positioning AI driven solutions to optimise outcomes within your functional domain. - 8+ years of experience in customer facing technical roles such as professional services consulting. What the work actually looks like: - Serve as a dedicated technical advisor for strategic enterprise customers over extended engagements, described in the posting as six months, one year or longer. - Act as the customer's go to expert for all matters relating to their Zscaler environment. - Work embedded within the customer's organisation rather than rotating across many accounts. How this differs from Zscaler's other customer facing roles on this board: escalation engineers handle the hardest cases across many customers as they arrive, and Center of Excellence engineers build the tooling and processes behind them. A resident consultant is assigned to one customer for a long stretch. Same product depth, very different day to day rhythm and relationship. What Zscaler says about the environment: an AI forward enterprise, cloud native Zero Trust Exchange platform, with a culture it describes around impact over activity, honest debate, customer obsession and accountability. Location and working pattern: Mumbai. Resident consulting typically means significant time at the customer site, so clarify what the arrangement looks like for the specific account before accepting. Honest fit guidance: the deciding question is not technical, it is temperamental. If you like building a deep relationship with one customer's environment, knowing its history and its quirks, and being the person they call, this is unusually satisfying work. If you would find that confining, the escalation or Center of Excellence roles at the same company suit better and are also on this board. Eight years of genuinely customer facing technical work is the bar, so pure internal engineering experience will not map cleanly.
What the posting requires: - 8 to 10 or more years of experience in solutions architecture, technical consulting or enterprise SaaS implementations. What this kind of role typically involves at an enterprise SaaS company, based on how the posting frames it: - Owning the technical relationship with customers through implementation and adoption. - Designing how the platform integrates with the customer's existing systems and processes. - Translating business requirements into a technical configuration and integration approach. - Working alongside sales, customer success and product teams. ⚠️ The geography matters here. NAMER in the title means the accounts are North American while the role is based in Pune, so working hours are likely to be shifted to overlap with North American time zones. Confirm the expected shift pattern early in the process, because it is the single largest lifestyle factor in this role and the posting does not spell it out. About the employer: Mindtickle is a revenue enablement platform used by sales organisations for onboarding, training, coaching and readiness. Its engineering and delivery presence in India is in Pune, where it also lists other technical roles. Location and working pattern: Pune, Maharashtra. Office days are not stated in the posting. Honest fit guidance: this is a customer facing technical role, so the skills being bought are as much communication and structured thinking as they are technical depth. If you have implemented enterprise SaaS for large customers and can hold a room of stakeholders through a design decision, the 8 year bar is a fair reflection of the seniority. If you want to write product code, this is not that job. Because the posting is light on a detailed requirements list, ask for specifics on the tech stack, the size of accounts, and the split between pre-sales and post-sales work before investing in the process.
What the posting requires: - 9+ years of relevant experience with a Bachelor's or Master's degree in Computer Science or Electrical Engineering, or 6+ years with a PhD. The posting states this tradeoff explicitly, which is unusual and worth noting if you hold a doctorate. - Extensive experience designing, building and operating distributed data platforms at large scale, with Spark, Kafka and Flink named. - Proficiency in Java, Scala or Python, along with strong data processing and SQL querying skills. - A proven track record of designing and optimising both batch and real time data pipelines. - Strong collaboration skills, with the ability to work with product managers, data scientists and engineers. - Advanced problem solving and analytical skills. What the work actually looks like: - Design, build and operate the distributed data platforms that Airbnb's internal business technology runs on. - Build and optimise batch and real time pipelines feeding analytics and operational systems. - Partner with product managers, data scientists and engineers across the BizTech organisation. About the team: BizTech provides reliable corporate tools, products and technical support for teams across Airbnb, and describes its purpose as driving technical breakthroughs that deliver value for the business and its people. It is internal platform work rather than guest or host facing product. Location and working pattern: Bangalore, India. This is the Bangalore based role. Airbnb does list some genuinely remote India positions in other teams, but this posting is location based, so do not assume remote. Honest fit guidance: the PhD clause is the detail most people will skim past, and it materially changes who should apply. At 9 years without one, or 6 with one, this is a senior individual contributor data engineering role at a company whose data volumes are genuinely large. The named technologies are conventional for the discipline, so the differentiator in an application will be evidence of having operated these platforms in production rather than only built on top of them.
What the posting requires: - 10+ years of experience working on software and operating distributed systems, with deep Kubernetes expertise including designing or evolving multi cluster platforms. - Proficiency in Python, Go or a similar programming language. - Understanding of workload isolation at the systems level: containers, virtual machines, and the tradeoffs between them for running untrusted code. - A customer focused mindset. - Valuing efficiency in processes and operations, with a strong preference for automation over manual processes. What the posting sets as position expectations: - Own the reliability architecture of the platform across regions and cloud providers. - Collaborate with the teams building the platform, providing internal support and guidance on operability, capacity and best practices. - Set operational standards for the team: on call quality, incident response and service level objective discipline. - Mentor and technically develop the SRE team. - Participate in a 24 by 7 on call rotation to resolve issues involving platform infrastructure. ⚠️ The on call commitment is stated plainly as a 24 by 7 rotation. At staff level that usually means you are also the escalation point for others' incidents. Weigh it honestly against the seniority and scope on offer. The detail worth noticing: the requirement about running untrusted code tells you something about the platform. Isolation tradeoffs between containers and virtual machines only become a live question when you are executing code you did not write, which makes this a more interesting systems problem than standard service reliability work. Location and working pattern: the posting states MongoDB is looking for candidates based in Bengaluru for its hybrid working model. Honest fit guidance: ten years plus deep multi cluster Kubernetes is a high and specific bar. The distinguishing experience is having designed or evolved multi cluster platforms rather than operated a single one, and being able to talk about isolation tradeoffs concretely. If you have that, the scope here, reliability architecture across regions and clouds, is genuinely staff level rather than a retitled senior role.
What the posting requires: - 10+ years of overall industry experience, with 6+ years shipping and sustaining production C++ (C++11 and later, including 14, 17 and 20): multi threaded, memory conscious, cross platform code. - Solid distributed systems fundamentals: routing, failover, backpressure, graceful degradation, and the failure modes that come with them. - Deep experience building and sustaining endpoint, client or systems software. - Expertise with data structures, algorithms and performance profiling. - Fluency with agentic coding systems and genuine curiosity about agent harnesses. - A BSCS or equivalent is required, with MSCS or equivalent preferred. What the work actually looks like: - Build and harden the C++ client runtime at the core of the product: lightweight, multi threaded, cross platform, macOS first then Windows. - Architect the distributed systems that keep it fast and resilient at scale, engineering for fault tolerance so failures degrade gracefully rather than breaking a session. - Build a secure agentic harness for safe, high performance execution. - Own reliability, observability, security and performance of the runtime across real, varied hardware. - Set patterns and standards for the endpoint codebase. Why this is a harder problem than it sounds: an endpoint agent runs on hardware you do not control, alongside software you did not choose, and it cannot fail loudly without breaking someone's working day. The posting's emphasis on graceful degradation and varied real hardware is the honest description of that constraint. Levelling: the title spans Staff and Senior Staff, and Netskope's postings state that teams hire across levels with candidates individually assessed and levelled on skills and experience. Location and working pattern: Bengaluru. Netskope describes open desk office layouts, so expect an in office team. Office days are not stated. Honest fit guidance: the 6 years of production C++ is the filter, and it means shipped and sustained rather than studied. Modern C++ across macOS and Windows with real multi threading is a narrower skill than a general backend background, and people who have it are in demand. If that is you, this is one of the more technically serious roles on today's board.
What the posting requires as minimum: - 10+ years of engineering experience, with 5+ years of hands on experience building and operating data systems and pipelines, datasets and data warehouses, infrastructure, and leading small teams to deliver solutions. - A strong engineering background and a genuine interest in data. - Prior experience writing and debugging data pipelines using a distributed data framework such as Spark, Hadoop or Trino. - An inquisitive nature, diving into data inconsistencies to pinpoint issues and resolve deep rooted data problems. Stripe states that the preferred qualifications are a bonus rather than a requirement, and that if you meet the minimum requirements you are encouraged to apply. What the work actually looks like: - Lead the technical outcomes for a team of engineers working on high impact, cutting edge data problems. - Build and operate data pipelines at large scale using the modern data engineering toolchain: Airflow, Spark, Kafka and Flink are named in the posting. - Collaborate with other Stripe teams to understand their use cases and unlock new capabilities for them. - Build strong working relationships across the company, which the posting treats as a core requirement rather than a soft extra. What the emphasis on empathy tells you: for a staff role at this scale, most of the hard problems are cross team. The posting naming empathy and relationship building alongside Spark and Kafka is a signal about how the role is actually evaluated. Location and working pattern: Bengaluru, India. Office days are not stated in the posting. Honest fit guidance: ten years is a real bar and the 5 years of hands on data systems work is the substantive part. The phrase leading small teams appears in the minimum requirements, so this is a technical leadership role even though it is an individual contributor title. If your data engineering has been solo or within one team, the cross organisation scope is the stretch. If you have led data platform work that other teams depended on, that is exactly the story to tell.
What the posting requires: - 10+ years of overall software and integration engineering experience, with 8+ years focused on API and enterprise integration. - 4+ years in a senior, lead or architect capacity, owning API and integration designs, patterns and technical decisions. What the work actually looks like: API and integration architecture: - Own the API and integration architecture and strategy for assigned domains, defining API led patterns across experience, process and system APIs, plus reference architectures and standards. - Design, build and evolve RESTful APIs with clear contracts, documentation and service level agreements for internal and external consumers. - Lead integrations between SaaS and on premises applications including NetSuite, Workday, Salesforce, Snowflake and ServiceNow. - Define non functional requirements and SLAs for APIs and integrations covering availability, latency, throughput, error budgets, RTO and RPO. - Drive observability and reliability by standardising logging, tracing, metrics, dashboards and alerting, and creating operational runbooks for incident response and post incident reviews. AI and intelligent automation: - Identify and prioritise AI opportunities within API and integration flows such as data enrichment, anomaly detection, routing, summarisation, classification and intent extraction. - Define safe and governed AI usage: clear input and output contracts for AI services, guardrails through prompt design, validation and constraints, handling of sensitive personal, financial and HR data in prompts and responses, and monitoring for model performance and drift in production. Governance and delivery: - Partner with security, compliance and audit teams so integrations, APIs and AI services meet security, privacy and regulatory requirements including SOX sensitive data flows, access control, encryption and audit trails. - Lead technical discovery and solution design for new initiatives with product managers, application owners and business stakeholders. - Own vendor and platform technical relationships, anticipating deprecations and coordinating upgrades and migrations. - Oversee CI/CD practice including branching and release strategy, automated testing and environment configuration across development, QA, UAT and production. ⚠️ Applying to Rubrik: rubrik.com returns 403 to automated requests, so this listing was verified live through the Greenhouse jobs API rather than by fetching the page. It opens normally in a browser. Location and working pattern: Bangalore, India. Office days are not stated. Honest fit guidance: the AI governance section is the part that will separate applications, because plenty of engineers have integration depth and far fewer have put guardrails around AI in a SOX sensitive flow.
What the posting requires: - A Bachelor's or Master's degree in Computer Science, Engineering, Information Systems or a related field. - 10 to 15+ years in data engineering or platform architecture, with a shift toward high level technical leadership. - Strong experience designing and implementing modern data architectures and cloud data platforms. - Deep hands on expertise in full stack development including frontend and backend technologies, and DevOps infrastructure. - Experience with Snowflake, Tableau or similar technologies. - Expertise in AI and ML platforms, and the engineering required to support generative AI at scale. What the work involves, based on how the posting frames the role: architecture ownership across Rubrik's AI data platform, meaning the design of the data foundations and the platform engineering that generative AI capabilities are built on, rather than building individual features. The breadth requirement covering frontend, backend and DevOps suggests the architecture spans a full product surface rather than one layer. What kind of role this is: an architect title with an explicit expectation of high level technical leadership means influence, standards and direction setting, with hands on credibility as the entry ticket. If you want to be writing production code most days, an architect seat at this level is usually not that, and the posting is honest about the shift it expects. ⚠️ Applying to Rubrik: rubrik.com returns 403 to automated requests, so this listing was verified live through the Greenhouse jobs API rather than by fetching the page directly. It opens normally in a browser. About the employer: Rubrik builds data security and cyber resilience software for enterprises, protecting and recovering data across cloud, SaaS and on premises environments. Location and working pattern: Bengaluru, India. Office days are not stated in the posting. Honest fit guidance: the breadth is the thing to be honest with yourself about. Data platform architecture plus full stack plus DevOps plus generative AI at scale is a lot of surface, and few people are genuinely deep in all of it. Treat the data architecture and AI platform experience as the core, and the rest as areas where working knowledge and good judgement will do. If your background is purely data warehousing without the AI platform side, that is the gap the posting cares about most.
What the posting states: - Successful candidates for this position typically have 10 to 15 years of experience in a customer or partner facing technical role. The posting frames this as typical rather than an absolute cut off, which is worth knowing if you are close to the range. - A self starter, technically capable professional comfortable operating with autonomy. What this kind of role involves, based on how the posting frames it: enabling global system integrator partners in India to build practices around Datadog, which typically covers technical enablement of partner engineers, supporting partner led solution design, building reference material and demonstrations that partners can reuse, and acting as the technical bridge between the partner organisation and Datadog's own teams. Why the GSI focus changes the job: working through system integrators is different from selling to a customer directly. Your leverage comes from making other organisations capable rather than from personally delivering, so the skills that matter most are teaching, structuring reusable material, and building trust inside a partner's delivery practice. Prior experience working with or inside a system integrator is the most relevant background you can bring. About the product context: Datadog's platform covers infrastructure monitoring, application performance monitoring, log management and security monitoring, so technical credibility here means being able to hold a conversation about how an engineering organisation actually observes and debugs its systems. Location and working pattern: Bangalore, India. Office days are not stated in the posting. Honest fit guidance: at 10 to 15 years this is a senior seat, and the partner lens is the differentiator rather than the product knowledge, which can be learned. If your experience is solutions architecture for direct customers only, the partner motion, co-sell, practice building and enablement, is a genuinely different muscle and worth addressing directly in your application. Because the posting is light on a detailed responsibilities list, ask early about which partners you would cover and how success is measured, since partner roles vary widely on that.
What the posting requires: - 10+ years of successful experience in customer facing technical sales or consulting roles focused on enterprise database technologies and cloud. - A Bachelor's degree in Computer Science, Engineering, or equivalent experience. Core expertise, with deep technical proficiency required in: - Microsoft SQL Server: architecting and managing large scale high availability and disaster recovery solutions, including extensive experience with Always On Availability Groups, Failover Cluster Instances and log shipping. - Cloud databases: design and management of Azure SQL and Azure SQL Managed Instance. What this kind of role involves: acting as the deep database specialist in customer engagements, designing how enterprise SQL Server estates are protected and recovered, and advising customers on architecture decisions that carry real consequences if a recovery is ever needed. Rubrik's product is data security and cyber resilience, so the conversations are about backup, recovery, ransomware resilience and business continuity for databases that organisations cannot afford to lose. Why the specialism is worth noting: HADR architecture for SQL Server at enterprise scale is a genuinely narrow skill. Most database professionals administer, fewer architect availability groups and failover clusters, and fewer still can do that while sitting in front of a customer explaining the tradeoffs. If you are in that overlap, roles like this are where that combination is valued most. ⚠️ Applying to Rubrik: rubrik.com returns 403 to automated requests, so this listing was verified live through the Greenhouse jobs API rather than by fetching the page directly. It opens normally in a browser. Location and working pattern: Bengaluru, India. Office days are not stated in the posting. Honest fit guidance: read the customer facing technical sales or consulting phrasing carefully. This is a pre-sales and consulting seat, so commercial outcomes are part of how it is judged, and the technical depth is what earns the right to be in the room. If you are a SQL Server DBA who enjoys the customer facing side, this is a natural next step. If you want to stay purely hands on inside one estate, it is not.
What the posting requires: - 12+ years of production level experience in one of Python, Java, Scala, C++ or a similar language. - Experience developing large scale distributed systems from scratch. - Hands on experience developing and operating backend systems. - The ability to contribute effectively throughout all project phases, from initial design and development through implementation and ongoing operations. What the work actually looks like at this level, based on how Databricks describes its staff engineering: - Deliver highly scalable, available and fault tolerant systems processing very large data volumes across thousands of customers. - Low level systems debugging, performance measurement and optimisation on large production clusters. - Build architecture designs, influence the product roadmap, and take ownership of new projects. - Help prevent and investigate production issues. - Plan and lead complex technical projects spanning several teams within the company. - Break complex problems quickly into potential solutions, knowns and unknowns, and de risk them through prototyping and validation. The scale you would be working at, in the company's own terms: millions of virtual machines, terabytes of logs and exabytes of data processed daily, with hardware, network and operating system faults treated as expected conditions rather than emergencies. Location and working pattern: Bengaluru. Databricks says it is in the process of setting up new teams from scratch at this site, so expect an in office or hybrid arrangement. The number of days is not stated in the posting. Compliance note in the posting: the standard Databricks export controlled technology clause applies. Where access to export controlled technology or source code is required, applying for a US government licence is at the employer's discretion, and it may decline to proceed with an applicant on that basis alone. Honest fit guidance: twelve years is the real bar and it is the highest on this edition. What distinguishes an application at this level is not more of the same experience but evidence of having led complex, multi team technical projects and having made architectural calls that survived contact with production. If you are at eight to ten years, Databricks has several roles on this board at that level, and stretching for this one is unlikely to clear the filter.
Added July 26, 2026
What the posting requires: - 3 to 6 years in software or ML engineering, with at least one full cycle on premises or enterprise deployment delivered end to end. - Production grade experience with Python, Docker, Linux systems administration, REST APIs and CI/CD pipelines. - Hands on experience with LLM inference stacks such as vLLM, TGI or Ollama, plus RAG architectures and vector stores. - Experience deploying in constrained environments: air gapped networks, limited connectivity, non standard hardware or complex regulatory requirements. - Full stack debugging instinct, comfortable diagnosing across infrastructure, networking and application layers without a specialist to hand. - Demonstrated ability to ship and maintain a working system end to end where reliability was non negotiable. - Proven ability to navigate ambiguous client requirements and make the call without explicit guidance. Nice to have: - Prior experience with strategic or complex enterprise accounts. - MCP server experience or familiarity with agentic frameworks. - Open source projects, side products or entrepreneurial stints showing technical craft and sustained follow through. What the work actually looks like: - Own end to end deployment of Sarvam's full AI stack in client environments, including on premises, air gapped and classified infrastructure. - Serve as technical single point of contact for assigned accounts, from scoping and proof of concept to steady state operations. - Diagnose and resolve integration failures, model drift, inference issues and infrastructure breakdowns without escalation ladders. - Manage deployment pipelines, model serving and environment configuration in constrained settings. - Drive client side adoption through documentation, training and operational handover. - Own client satisfaction, time to value and uptime for your accounts, and flag risks before they become escalations. - Feed field learnings back into the product and the replicable deployment library. What they say about the person: the posting asks for someone who treats ambiguity as the baseline, owns outcomes rather than tasks, and operates in forward deployed environments without daily oversight. It also says plainly that you are expected to be available and responsive when your clients are, which is worth weighing. Location and working pattern: Delhi, embedded with client teams. No remote or hybrid arrangement is stated. Honest fit guidance: this is the most accessible role on today's board by years, but it is not an easy one. The deciding requirement is the full cycle deployment you have already delivered, not the year count. If your experience is building features inside one company's own environment, the constrained deployment requirement will be the gap. No interview process is published.
What the posting requires: - A PhD in Machine Learning, Computer Science or a closely related field, or in the final stages of completion. - 3+ years of research experience post PhD, or equivalent depth. The posting adds that exceptional early career candidates with a strong research record will be considered, so the years figure is not an absolute gate. - First author publications at top tier ML venues such as NeurIPS, ICML, ICLR, ACL, EMNLP or COLM. - Hands on experience pre training transformer based language models from scratch, ideally at 7B parameters or more. The posting says you should be able to describe a training run you owned end to end, including what went wrong and how you debugged it. - Meaningful contributions to the open source LLM ecosystem: research code, model releases, datasets or substantive contributions to widely used projects. - Fluency in PyTorch and comfort with distributed training. You should be able to read a training loop and immediately see where it might be slow, unstable or wrong. - Strong intuition for experimental design: knowing what to measure, what to ablate, and what scale a result needs to hold at before it can be trusted. Nice to have: - Work on novel architectures such as mixture of experts, state space models or hybrid architectures, or non trivial modifications to standard transformers. - Experience with multilingual or multimodal pre training. - Research contributions in post training: RLHF, RLVR, distillation or reasoning models. - A track record of taking a research idea from prototype to a shipped capability. What the work actually looks like: - Drive open ended research on architecture, optimisation, scaling behaviour, training stability and post training recipes for the next generation of foundational models. - Design and execute ablations at scales that genuinely inform large run decisions, including running pre training experiments end to end yourself. - Translate findings into concrete proposals for the next training run, and own those proposals through to production. - Work directly with the infrastructure and data teams, since many of the important research questions live at that boundary. - Read broadly, write internally, and publish externally when the work merits it. Why the role is framed as rare: the posting says you would be one of a small number of people in the world making architectural and training recipe decisions on a frontier scale model run, with the compute and autonomy to back it up. Location and working pattern: Bengaluru. No remote or hybrid arrangement is stated. Honest fit guidance: the 3 year figure is genuinely low for the seniority of the work because it is counted after a PhD. If you do not have a PhD and a first author publication record, this specific posting is not the one to spend an application on, whatever your industry experience.
What the posting requires as mandatory: - A B.Tech, M.Tech or PhD in Computer Science, Electrical Engineering, Statistics, Mathematics or a related field. - 5+ years of experience in data science, analytics or a closely related domain. - Strong foundation in probability, statistics and estimation theory. - Strong programming in Python, with solid fundamentals in object oriented programming, algorithms and data structures. - Deep familiarity with SQL, complex query writing, indexing and database internals, plus working knowledge of at least one NoSQL store. - Experience with data visualisation and analytical storytelling. - Excellent written and verbal communication. - Familiarity with AI powered tools for analytics and software development, including using them for exploratory data analysis, experiment analysis and documentation, and critically evaluating AI generated output for correctness, statistical validity and reproducibility. Preferred skills: - Exposure to cloud platforms and services such as AWS Kinesis, EKS and autoscaling systems. - Experience building lightweight web or service components with Flask or Django. What the work actually looks like: - Design, implement and maintain offline and online evaluation frameworks for AI and ML features. - Define, validate and evolve the KPIs, success metrics and audit methodologies used across teams. - Perform deep error analysis, bias analysis and segmentation to identify failure modes. - Own golden datasets, validation protocols and benchmarking standards. - Conduct large scale analytical studies on feature performance, data quality and system behaviour. - Design and review experiments including offline evaluations, controlled rollouts and A/B tests, ensuring statistical correctness. - Perform post deployment monitoring and regression detection. - Build tools, dashboards and automation to scale audits and reporting, and enable self serve analytics. - Mentor junior data scientists on statistical rigour, experiment design and analytical storytelling. Location and working pattern: Bangalore. This posting does not state the number of office days, though some other Netradyne listings specify a five day on site model, so ask. A note on the employer: Netradyne postings carry a recruitment fraud warning. Official communication comes only from netradyne.com or us-greenhouse-mail.io addresses, and the company never charges candidates a fee. Honest fit guidance: if you want to build models, this is explicitly not that role. It suits someone who is happier proving whether a system works than building it, and who can tell a product team its metric is wrong.
What the posting requires: - 5+ years on ML deployment, with 2+ years specifically on Intel inference stacks. - Production OpenVINO experience, including model conversion, accuracy validation after quantisation, and driver version pinning. - ONNX Runtime execution provider knowledge: when to use the OpenVINO EP versus native OpenVINO, and when to fall back to the CPU EP. - x86 CPU profiling and optimisation with VTune and perf, including comfort reading hot loops at the assembly level when needed. Noted as a strong plus rather than a requirement: - AVX-512 or AMX intrinsics. Bonus points: - Direct prior interaction with the OpenVINO team or Intel ecosystem partners. - Custom OpenVINO operator authoring. What the work actually looks like: - Land Sarvam's edge models on Intel NPU, discrete GPU and integrated GPU inside defined service level agreements. - Own the OpenVINO build and quantisation recipe for the team's models, including the driver version compatibility matrix. - Drive x86 CPU optimisation for the universal fallback path, covering AVX-512, AMX and threading strategy. - Own the Intel device CI pool and regression detection across OpenVINO upgrades. The hardware surface named in the posting: Intel NPU via OpenVINO on Meteor Lake, Lunar Lake and vPro AI PCs, Intel integrated and discrete GPU via OpenVINO and ONNX Runtime, and x86 and AMD64 CPU for fallback paths. Location and working pattern: Bengaluru. No remote or hybrid arrangement is stated. Honest fit guidance: the 2 years on Intel stacks specifically is the real filter, not the 5 years overall. General ML engineering or even CUDA and Nvidia deployment experience does not substitute, because the entire job is the Intel toolchain and its quirks. If you have that background it is a rare seat, since few teams in India run this surface at production scale.
What the posting requires: - 5 to 8 years of experience in security engineering, information security or a compliance focused role. What the work actually looks like, which is where this posting is unusually detailed: Compliance programme ownership: - Own and manage Hevo's compliance certifications end to end, including SOC 2 Type II, ISO 27001, GDPR and other applicable frameworks, across audit cycles, evidence collection and remediation. - Lead internal readiness assessments and gap analyses, and drive remediation roadmaps with Engineering and Infrastructure. - Act as primary point of contact for external auditors, certification bodies and customer security review teams. - Respond to customer security questionnaires, due diligence requests and vendor assessments. Security engineering and controls: - Design, implement and continuously improve security controls across cloud infrastructure, access management, data handling and the software development lifecycle. - Work with DevOps and Engineering to embed security and compliance requirements into CI/CD pipelines, infrastructure as code and deployment practice. - Conduct security risk assessments, vulnerability reviews and internal audits, prioritising findings and driving resolution to deadlines. - Define and enforce policies on data classification, access control, encryption, logging, monitoring and incident response. Policy and governance: - Develop and operationalise security policies, standards and procedures aligned to industry frameworks. - Build and run a compliance awareness and training programme across the company. - Establish continuous compliance monitoring using GRC tooling and automation. - Report compliance metrics, audit findings and risk posture to leadership on a regular cadence. Cross functional work: - Assess compliance implications of new features and infrastructure changes early with Product and Engineering. - Work with Legal and Finance on contractual obligations, data processing agreements and regional regulatory requirements. - Support Sales and Customer Success on enterprise security reviews for security sensitive deals. Location and working pattern: Bengaluru. Office days are not stated. Honest fit guidance: this sits deliberately at the intersection of security engineering and compliance, and the posting calls it high visibility. If you are a pure penetration tester or a pure GRC analyst, only half the role will fit. It suits someone who can both write the policy and change the pipeline that enforces it.
What the posting requires: - 5 to 8 years of experience in a quantitative analyst role, preferably in B2B SaaS, growth analytics or revenue operations. - Proficiency in SQL and experience working with large datasets. - Experience using Tableau, Looker or similar tools to build dashboards and report insights. - Strong communication skills, with the ability to present data to both technical and non technical audiences. - Ability to manage multiple projects simultaneously and drive deliverables with minimal oversight. - Attention to detail, a diagnostic approach to problems, a continuous learning mindset, and the ability to solve complex, open ended problems. Nice to have, listed as a bonus: - Experience with executive or revenue operations reporting. What the work actually looks like: - Query large datasets using SQL to extract and manipulate data. - Maintain and optimise databases on the data warehouse. - Prepare and present weekly business reviews, forecasts and key metric tracking. - Drive analytics projects on customer funnels and lead acquisition, uncover insights and report findings to leadership. - Collaborate with cross functional teams to execute weekly business reviews and track follow up actions. - Lead and manage end to end analytics projects with minimal oversight, and mentor junior team members. - Continuously challenge and improve metrics by aligning them with industry standards. About the company: Hevo is based in San Francisco and Bangalore, has raised $42 million from Sequoia India, Qualgro and Chiratae Ventures, and powers data analytics for more than 2,000 companies. Its stated mission is building technology from India for the world that is simple enough that anyone can unlock the potential of their data. Location and working pattern: Bengaluru. Office days are not stated. Honest fit guidance: this is analytics for the business, not pipeline engineering. If you want to build ETL, look at the data engineering roles on this board instead. If you are strong in SQL and can hold a room of executives through a weekly business review, the fit is direct. No interview process is published.
What the posting requires: - Ideally 5 to 10 years of related experience in a customer facing role, with a minimum of 2 years in pre-sales with enterprise software. - A minimum of 3 years with modern scripting languages such as Python, Node.js or SQL, or popular programming languages such as C, C++, Java or C#, in a professional capacity. - Experience designing scalable and highly available distributed systems, in the cloud and on premises. - Demonstrated ability to review the complex architecture of existing applications with customers and advise on improvements. - Excellent presentation, communication and interpersonal skills, able to convey complex technical and business concepts clearly to both technology and business leadership. - Ability to strategise with sales teams and recommend how to drive a multi threaded account strategy. - Ability to travel up to 25 percent. - A Bachelor's degree or equivalent work experience. Nice to have: - Experience selling databases or deploying applications with a major cloud provider. - Experience with database programming and data models. - Experience in data engineering or AI and ML projects. - Experience transforming legacy systems into modern, scalable stacks. - Understanding of sales methodologies such as MEDDPICC or Command of the Message. - A MongoDB certification or a cloud provider certification. What the work actually looks like: - Design scalable and performant applications, systems and infrastructure for large software projects using MongoDB. - Guide customers on architecture patterns and optimisation strategies, and articulate business value to the relevant stakeholders. - Collaborate with the sales team on account planning, opportunity qualification and pipeline strategy, owning the technical aspects including discovery, demos, proof of value, presentations, sizing and documentation. - Generate demand within the territory through technical initiatives, trade shows and account based marketing events. - Build customer relationships and champions, and relay field feedback to the product team. - Mentor other Solutions Consulting team members. Location and working pattern: the posting states MongoDB is looking for candidates based in Mumbai for its hybrid working model. Honest fit guidance: this is a pre-sales seat, so revenue is part of how the role is judged. But unlike many roles with this title, it asks for real coding and distributed systems design experience, which is why it is on this list. If you want to write production code full time, it is not the right move.
What the posting requires: - 5+ years of pre-sales experience with enterprise software, and technical aptitude. - 3+ years of software development experience. - Working knowledge and ability to code with one or more modern scripting languages such as Python, Node.js or SQL, or popular programming languages such as C, C++, Java or C#. - Working knowledge of UI development with demonstrable skills in semantic HTML, modern CSS and TypeScript, integrated with a framework such as Vue.js, React.js or Angular.js. - Demonstrated working knowledge of using AI agents such as Cursor, v0, Lovable or Windsurf to orchestrate UI designs and interfaces. - Proficiency deploying applications to the cloud with DevOps best practice, ideally AWS. - Experience with benchmarking, profiling and performance tuning of database systems. - Excellent presentation and communication skills. - A Bachelor's degree or equivalent work experience. Nice to have: - Experience selling databases or deploying applications with a major cloud provider. - Experience with database programming and data modelling. - Knowledge of modern technologies and their integration requirements, such as React.js, cloud storage, API management, Kafka and serverless. - A cloud provider certification or a MongoDB certification. What the work actually looks like: - Work with advisory consulting partners on reference architectures, patterns and technical blueprints for making the best use of MongoDB. - Articulate the business value of MongoDB solutions and bridge that to technical value. - Partner with account teams to support accounts from small startups to large enterprises. - Support sales through technical discovery, demos, proof of value, presentations, sizing and documentation of technical decision criteria, across several opportunities in parallel. - Act as a liaison, gathering field feedback and relaying it to Product Management. - Build and maintain relationships with technical partners, influencing their decisions and reinforcing how MongoDB adds value to their clients. - Drive partner Center of Excellence strategies and create demand for MongoDB solutions. - Mentor other pre-sales team members and share best practice. Location and working pattern: listed as India, without a specific city. Confirm the base location and any hybrid expectation with the recruiter. Honest fit guidance: the partner lens is the differentiator here, so experience working with or inside system integrators and consulting partners matters as much as the technical list. The coding and UI requirements are genuinely enforced by the posting, so this is not a slide deck role.
What the posting requires as mandatory: - A B.Tech, M.Tech or PhD in computer science, electrical engineering or a related area. - 6.5+ years of research or industry experience within computer vision and machine learning models. Note this is higher than the Senior in the title implies, and the body of the posting refers to the role as Staff Research Engineer. - In depth understanding of machine learning, both deep learning and classical ML, and of computer vision concepts. - Excellent programming skills: Python is required, C++ is desired. - Ability to take abstract product concepts and turn them into reality. - Ability to innovate on cutting edge problems without documented solutions. - Hands on experience handling edge deployments targeting various hardware platforms. Preferred skills: - Experience with time series data. - Experience with camera calibration, multi view geometry, 3D reconstruction and SLAM. - Experience with road scene understanding: objects, lanes, intersections, signs. - Experience successfully applying machine learning to a real world problem. - Experience conducting successful statistical experiments. What the work actually looks like: - Help design, implement and commercialise driver monitoring and driver assistance algorithms. - Work with very large datasets and deploy new algorithms and models into thousands of vehicles. - Design and commercialise algorithms characterising driving behaviour. - Design, implement and track key metrics, and architect data driven solutions. - Improve the machine learning infrastructure for scalable training and inference. - Innovate and develop proof of concept solutions showcasing novel capabilities. About the team: Netradyne describes its Analytics team as comprising graduates from IITs, IISc, Stanford, UIUC and UCSD. Location and working pattern: Bangalore. This posting does not state the number of office days, though some other Netradyne listings specify a five day on site model. A note on the employer: Netradyne postings carry a recruitment fraud warning. Official communication comes only from netradyne.com or us-greenhouse-mail.io addresses, and the company never charges candidates a fee. Honest fit guidance: treat this as a staff level computer vision role, because the posting body does. The edge deployment requirement is the part people underestimate: this is vision that has to run on a device in a truck, not in a notebook.
What the posting requires: - A B.E, B.Tech, M.E or M.Tech degree with a minimum of 6+ years of experience in software system optimisation. - Proficiency in C and C++, OpenGL, CUDA and Python. - A solid grasp of basic statistics, probability, and machine learning and computer vision concepts. - Experience with ML frameworks including Caffe, TensorRT, OpenCL, SNPE, OpenVINO and ONNX. - Exceptional attention to detail, strong analytical skills and a creative mindset directed at system performance. Described as a valuable asset rather than required: - Experience with embedded platforms, make files and build systems, and familiarity with Jenkins. What the work actually looks like: - Craft and develop tools, frameworks and reporting mechanisms for system optimisation. - Streamline software for deployment across IoT devices, implementing on GPU, CPU and DSP. - Enhance data platforms and optimise the machine learning models deployed on the platform. - Improve driver monitoring and driver assistance algorithms to boost system efficiency, and report the key performance indicators. - Manage production inquiries and ensure overall application stability in production environments. - Convey highly technical results to diverse audiences. Location and working pattern: Bangalore. Office days are not stated in this posting. A note on the employer: as with Netradyne's other listings, the posting carries a recruitment fraud warning. Official mail comes only from netradyne.com or us-greenhouse-mail.io addresses, and the company never asks candidates for fees or for sensitive data over unsecured channels. Honest fit guidance: this is the inference optimisation and embedded deployment end of ML, not model research. If your background is training models in Python and you have never profiled something on a DSP or converted a model through SNPE or TensorRT, the framework list is the honest gap. If you have done that work, it is one of the clearer matches on today's board.
What the posting requires: - 6+ years of experience, including producing high quality production code and detailed technical design documents for distributed systems. - Proven ability to break down complex, multi month projects into actionable milestones and tasks. - Solid grasp of industry best practice for distributed systems: monitoring, documentation, testing and finish quality. - Experience optimising cloud resource utilisation or developing large scale distributed tools. - Ability to make well reasoned trade offs between system performance, development velocity and technical debt. What the work actually looks like: - Lead projects from concept to deployment, designing and building scalable systems that handle high volume data streams for cost attribution and resource management. - Identify and eliminate inefficiencies in the cloud architecture, engineering solutions that mitigate resource waste and improve attribution accuracy. - Act as technical expert and owner for your service area across its full lifecycle, including code quality, monitoring and operational overhead. - Work with product and infrastructure teams to turn business needs into technical specifications, and build tooling that simplifies cloud economics for other engineers. - Contribute to code reviews, share engineering practice and mentor junior engineers. - Drive a shift left culture by integrating efficiency checks directly into the developer workflow. - Build automation and AI or agentic tooling that detects waste, attributes cost and remediates issues with minimal human intervention. The scale described: the team manages infrastructure efficiency across AWS, Azure and GCP for one of the world's largest data and AI platforms, with cloud spend in the hundreds of millions of dollars. Location and working pattern: Bengaluru. Databricks says it is still building out this site, so expect an in office or hybrid arrangement. The number of days is not stated. Compliance note in the posting: where a role requires access to export controlled technology or source code, Databricks says applying for a US government licence is at its discretion and it may decline to proceed on that basis. Honest fit guidance: cost and efficiency engineering is often dismissed as unglamorous, but at this scale it is a genuine distributed systems problem with a measurable outcome. If you have built large scale tooling and enjoy owning a service end to end, six years is a fair bar.
What the posting requires: - 6+ years of experience in data engineering, data platforms and analytics, or software engineering. - Comfort writing code in Python, Scala or JavaScript and TypeScript, and modern frameworks. - Working knowledge of two or more common cloud ecosystems (AWS, Azure, GCP), with expertise in at least one. - Deep experience with distributed computing using Apache Spark, including knowledge of Spark runtime internals. - Familiarity with CI/CD for production deployments. - Working knowledge of MLOps, ML and AI models, and AI APIs. - Experience designing and deploying performant production data architectures and applications combining data pipelines, ML and AI models, and user facing interfaces. - Experience with technical project delivery: managing scope, timelines and measurable outcomes. - Documentation and whiteboarding skills. - Experience working with enterprise clients and managing conflict across a broad stakeholder range. - Willingness to travel to customers about 20 percent of the time. - A Databricks certification. What the work actually looks like: - Lead customer technical projects, delivering production grade systems, reference architectures, custom applications, and data ingestion with ML and AI model integration. - Guide strategic customers through transformational big data projects, from end to end design through build and deployment. - Work with engagement managers to scope technical delivery with customer input. - Own architecture and design decisions, keeping solutions secure, scalable and aligned to both customer needs and Databricks best practice. - Embed with customer teams, engaging with stakeholders from individual contributors to executives. - Work with Databricks engineering and customer support to feed back product and implementation issues and drive rapid resolution. - Contribute accelerators, frameworks and best practices that scale across accounts and influence the product roadmap. Location and working pattern: Bengaluru, with roughly 20 percent travel to customers. Compliance note in the posting: the standard Databricks export controlled technology clause applies. Honest fit guidance: this is a hands on customer facing engineering role, not a solutions architect who only advises. The posting says it is for builders who thrive at the intersection of technology and business impact, and the billable framing is worth taking seriously: delivery to specification and to date is how the work is judged.
What the posting requires as minimum: - A Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience. - 6+ years of Salesforce development experience, including strong hands on expertise in Salesforce CPQ. - Strong understanding of Quote to Cash processes, sales workflows and Salesforce CPQ best practice. - Hands on experience with Apex, Lightning Web Components, Flows, SOQL, and REST and SOAP APIs. - Experience with product modelling, pricing rules, quoting workflows, approvals, amendments and renewals. - Experience integrating Salesforce with external systems such as ERP, billing, payment or other enterprise platforms. What the work actually looks like: - Design, build and support Salesforce CPQ solutions across product modelling, pricing, quoting, approvals, amendments and renewals. - Configure and enhance CPQ capabilities including product rules, price rules, bundles, product options, quote templates, discounting and approval workflows. - Partner with Sales Operations, Revenue Operations, Finance and Deal Desk to understand requirements and close process gaps. - Develop and maintain Salesforce solutions using Apex, Lightning Web Components, Flows, SOQL and platform APIs. - Build and support integrations between Salesforce CPQ and external enterprise systems. - Participate in technical design, story grooming, sprint planning, testing, code reviews, release management and production deployments. - Troubleshoot issues across CPQ configuration, pricing logic, automation, integrations and system performance. - Support documentation, user acceptance testing, regression testing and user enablement. - Ensure solutions align with security, data governance and Salesforce platform best practice. - Use AI powered engineering tools such as Cursor, Claude Code, Agentforce and GitHub Copilot to improve productivity, while applying sound judgement on security, accuracy and responsible use. Location and working pattern: the posting states MongoDB is looking for candidates based in Gurugram for its hybrid working model. Honest fit guidance: this is a specialist Salesforce CPQ role and the 6 years is specifically Salesforce development, not general software engineering. A backend engineer without CPQ experience would be applying against the core requirement. For an experienced Salesforce developer, working on the systems of a company like MongoDB rather than an agency is the draw.
What the posting requires: - 6+ years of software engineering experience, described as being a master of fundamentals. - Full stack versatility: able to move between frontend, backend and infrastructure and own features end to end. - Comfort designing user experience in React and diving into AWS to tune heavy video transcoding pipelines. - Ability to architect and scale cloud environments, including complex AWS infrastructure and ECS services. - Deep observability practice, with precise telemetry across CPU, memory, network and disk IOPS. - Ability to design and optimise data pipelines at scale. - Strong engineering intuition and architectural expertise, since the team leverages agentic coding models heavily and relies on human judgement for whether systems are built the right way. What the work actually looks like: - Own the technical execution for massive scale physical AI training data. - Lead technical development of Instawork Lens, the global data collection platform, and the dedicated QA platform, ensuring high throughput data enrichment, labelling and continuous quality assurance loops. - Architect and scale cloud environments, managing AWS infrastructure and ECS services for video transcoding. - Design and optimise data pipelines capable of operating at scale. - Act as a key engineering leader in the Bengaluru hub. What the business actually does, since it is unusual: Instawork Robotics Labs deploys skilled hourly workers into real commercial and residential environments to capture task data, which leading robotics labs then use to train their foundation models. The posting frames closing this data gap as the defining infrastructure challenge of the physical AI era. Location and working pattern: Bengaluru. Office days are not stated. Honest fit guidance: the posting asks for a generalist and means it, so specialists who have only worked in one layer will struggle against the breadth requirement. Video pipeline and transcoding experience is the part most candidates will lack. If you like owning infrastructure and product surface at once, and the physical AI data problem interests you, six years is a fair bar for the scope described.
What the posting requires: - 7 to 9 years of hands on experience in a DevOps, Site Reliability Engineering or Platform Engineering role. What the work actually looks like, grouped as the posting groups it: CI/CD and automation: - Design, build and maintain CI/CD pipelines supporting rapid, high quality delivery across multiple teams and environments. - Automate build, test, release and deployment workflows. - Own release management including versioning, tagging, rollback strategies and progressive delivery through canary and blue green deployments. - Integrate automated testing, code quality gates and security scanning into delivery pipelines. Cloud infrastructure and architecture: - Architect, provision and manage scalable cloud infrastructure across AWS, GCP or Azure using infrastructure as code tools such as Terraform, Pulumi or CloudFormation. - Design for high availability, fault tolerance and cost efficiency, and review and optimise cloud spend. - Manage multi environment setups across development, staging and production with environment parity. Containers and microservices: - Build and manage containerised workloads using Docker and Kubernetes on EKS, GKE, AKS or self managed clusters. - Define standards for container image builds, registry management, security scanning and image lifecycle. - Implement service mesh, ingress and networking within Kubernetes. - Drive adoption of Helm or Kustomize for repeatable deployments. Observability and reliability: - Build and maintain an observability stack covering metrics, logs and distributed tracing, using tools such as Prometheus, Grafana, Datadog, ELK or EFK, and Jaeger. - Define SLIs, SLOs and error budgets with engineering teams and lead SRE practice across the organisation. - Lead incident response including on call rotation and blameless post mortems. Security and compliance: - Embed security into infrastructure and pipelines: secrets management with Vault or AWS Secrets Manager, least privilege IAM, network segmentation and vulnerability scanning. Who you report to: the Director of IT and Information Security. Location and working pattern: Gurugram. Office days are not stated. Honest fit guidance: the breadth here is wide and genuinely staff level. An on call rotation is stated. ChargePoint notes it provides reasonable accommodations throughout the hiring process and gives an email address for such requests.
What the posting requires: - 7+ years of engineering experience, extensively with Django or Flask, React, and relational databases in a microservice based architecture. - A Bachelor's degree in Computer Science or Computer Engineering, stated as preferred. - Strong experience with AWS including Route53, CloudFront, API Gateway, Aurora RDS, DynamoDB, ElastiCache, EKS, ECS, S3, the AWS SDK, Lambda and SQS. - Proficiency writing unit and integration tests, with hands on experience across complete CI/CD tooling including Git, CI/CD tools and security scans. - Knowledge of Linux administration, comfortable with console commands, scripting and utilities such as Python and Bash. - Demonstrated experience building REST APIs and using OpenAPI or Swagger specifications. - Knowledge of Kafka or Flink. - Proven experience with agile development, CI/CD tools and project tracking tools, plus familiarity with gRPC, GraphQL and automation tools such as Ansible, Chef or Puppet. - Experience with third party integrations, and custom application development and deployment. - Proficiency across SQL and NoSQL stores including MySQL, Postgres, Redis, DynamoDB, ElasticSearch and MongoDB. - Experience with BI tools such as Tableau or Power BI. Desired rather than required: - Experience with large scale, technically complex accounts that constantly challenge product capabilities. - Demonstrated ability to communicate, present and influence at all levels of an organisation. What the work actually looks like: - Design, develop and maintain cloud native solutions and analytics dashboards for proactive monitoring and network hygiene. - Ensure appropriate documentation for all development and modification. - Ensure the integrity and security of institutional data. - Design data flow diagrams to define workflow, and data structure diagrams to refine database needs. - Translate software requirements into low level design, and evangelise clean architecture and clean code practice. - Perform code reviews, and help train, guide and lead others in building projects start to finish. Who you report to: the Director, NOC Delivery and Automation. Location and working pattern: Bengaluru, India. Office days are not stated. Honest fit guidance: the requirement list is long but the core is Python web services on AWS at senior level. Do not be put off by the breadth of named technologies, which reads more like a wish list than a checklist. The NOC context means the software has real operational consequences when a charger is down.
What the posting requires: - 8 to 12 years designing, building and troubleshooting distributed computing applications, with 4+ years delivering production scale Spark, ML or AI solutions in Python, Java or Scala. - 3 to 5 years in customer facing roles such as Technical Account Manager or Solutions Architect, with strong communication and relationship building. - Hands on expertise with data lakes, SQL based databases, and cloud data warehousing or ETL tools such as Snowflake, Redshift or BigQuery. - Deep knowledge of Spark core internals, Delta or Iceberg, JVM optimisation and memory management. - Proficiency in AI ecosystems including machine learning, deep learning and generative AI. - Practical experience with AWS, Azure or GCP, plus building and managing CI/CD pipelines, monitoring and alerting. - Proven ability to anticipate, identify and mitigate risk while planning solutions for production problems. - Proven ability to work with cross functional teams and senior leadership. What the work actually looks like: - Advanced troubleshooting and root cause analysis on performance and reliability issues across Spark, SQL, Delta, Streaming and Databricks runtime features, using Spark UI metrics, Mosaic AI Model Service, DAGs and event logs. - Work with R&D and network operations teams to define continuous monitoring that catches performance problems early in customer environments. - Build rapid proofs of concept, then test, deploy and monitor solutions. - Develop playbooks and maintain a knowledge base of common issues and solutions for Spark, ML and AI workflows. - Train customer engineering and business teams on performance tuning, debugging and platform features. - Advocate for customers in business review meetings as their trusted advisor and primary technical contact. - Work onsite with field engineering, sales and product teams during customer engagements and technical presentations. How this differs from the senior version of the same role, which is also on this board from an earlier edition: the staff posting raises the distributed computing requirement from 5 to 8 years up to 8 to 12, while keeping the same 3 to 5 years of customer facing experience. If you are between those bands, apply to the senior one. Location and working pattern: Bengaluru, with onsite collaboration during customer engagements. Compliance note in the posting: the standard Databricks export controlled technology clause applies. Honest fit guidance: both halves are required. Deep Spark internals without customer facing experience, or account skill without the ability to read an event log, will each fall short.
What the posting requires: - 8+ years of software engineering experience, with 4+ years focused on AI and ML systems in production. - A B.Tech, B.E. or M.S. in Computer Science, Machine Learning or a related field from what the posting describes as a top tier institution. - Deep expertise in Python, FastAPI, Django and modern backend frameworks for AI service development. - Hands on LLM engineering: LangChain, LangGraph, Amazon Bedrock or OpenAI APIs, prompt engineering and RAG architectures. - Strong Elasticsearch experience including vector search, hybrid search combining BM25 with dense embeddings, and semantic retrieval. - Proficiency with vector databases such as Qdrant, ChromaDB or Pinecone, and embedding based retrieval. - Experience building production LLM systems with a focus on low latency inference, caching strategies and observability. - Strong foundation in distributed systems design, microservices and event driven patterns with Kafka or RabbitMQ. - Experience with AWS or GCP, containerisation with Docker and Kubernetes, and CI/CD pipelines. - Strong knowledge of PostgreSQL including query optimisation and schema design, plus Redis, MongoDB and message queues. - A track record of optimising system performance with measurable improvements in latency or cost. - Experience with voice AI systems, telephony integrations such as Genesys or SIP, and speech processing pipelines. - Background in computer vision, image processing or visual transformer architectures. - Data engineering experience with Airflow, DBT and analytics platforms such as ClickHouse, Trino or Iceberg. - Experience with massive datasets, described as 50TB and above, and building scalable data pipelines. - Hands on experience with model fine tuning techniques such as LoRA or QLoRA. - Familiarity with RLHF style preference tuning and model alignment. - Experience with observability and monitoring stacks covering metrics, logging and tracing. - Certifications in generative AI, agentic AI or a related specialisation. What the work actually looks like: - Lead development of AI solutions across voice AI, computer vision and conversational AI. - Architect and build production grade AI systems that enhance the monitoring and analytics platform, improve customer support, and enable intelligent automation across the charging infrastructure. - Work with cross functional teams to design, build and deploy AI solutions affecting EV drivers and operators worldwide. Who you report to: the Director, NOC Delivery and Automation. Location and working pattern: Bengaluru, India. Honest fit guidance: this is a long requirement list even by staff standards, and the voice AI plus computer vision plus LLM combination is unusually broad. Treat the first block as the real bar and the rest as a preference list. If you have shipped production LLM retrieval systems and can talk about latency and cost numbers, apply.
What the posting requires as minimum qualifications: - A minimum of 8+ years of experience in technical support, with at least 5 years focused on DLP and CASB solutions and escalations. - A foundational understanding of AI and ML technologies, and experience leveraging, securing or positioning AI driven solutions within your domain. Zscaler describes itself as an AI forward enterprise and puts this first in its list. - Experience with data loss prevention, securing SaaS, and Cloud Access Security Brokers. - Practical working knowledge of AWS, Azure or GCP, paired with a strong understanding of Unix, Linux and Windows operating systems. - Deep understanding of data protection principles and practices. Preferred qualifications: - Experience deploying or supporting AI powered sensitive data discovery tools or automated data classification models to enhance DLP capabilities. - Experience with scripting and automation using Python or PowerShell. What the work actually looks like: - Serve as the primary point of contact for escalated DLP issues, providing advanced troubleshooting and resolution. - Take ownership of complex and critical cases through to effective resolution. - Perform detailed root cause analysis to identify underlying issues and implement long term solutions. - Work closely with product development, engineering and other cross functional teams to resolve issues and improve Zscaler DLP products and services. - Maintain clear and proactive communication with customers throughout the escalation, providing regular updates and managing expectations. Who you report to: the Senior Manager, Product Support, in the Support department. Location and working pattern: the posting states this is a hybrid role based in Bangalore. What they say about the person: the posting looks for someone comfortable in ambiguity, with an ownership mindset, a genuine growth mindset and an appetite for feedback. Zscaler frames its culture around impact over activity and constructive, honest debate. Honest fit guidance: the 5 years specifically on DLP and CASB is the real filter, not the 8 years overall. General network security support experience without DLP depth will not clear it. Unlike Zscaler's other escalation roles this one does not state a 24x7 on call rotation in the same terms, but escalation work in a TAC generally carries out of hours obligations, so confirm that before accepting.
What the posting requires: - 9+ years of experience across software engineering, network security and AWS security. Note that it is the combination that is being asked for, not nine years in any one of them. - A proven track record as an expert in the infrastructure security domain. What the work actually looks like: Leadership and strategy: - Develop and document comprehensive security policies, reference architectures, design patterns and the strategic roadmap for infrastructure security. - Keep abreast of current network and infrastructure security trends and best practice. - Collaborate with engineering, AWS and architecture teams so proposed designs meet both business objectives and stringent security requirements. - Partner with stakeholders across the organisation to stay current on infrastructure designs. Technical design and architecture: - Provide technical leadership to build security into all infrastructure and network designs across AWS cloud, SaaS applications and IT environments. - Design and re architect the AWS infrastructure to implement robust security measures, including network segmentation and secure access. - Build defence in depth, secure access and IAM from the ground up. - Address vulnerabilities and misconfigurations across operating systems, infrastructure and cloud. Operations and mentoring: - Work closely with security operations and incident response teams, providing technical leadership. - Mentor other junior infrastructure security professionals. Who you report to: the VP of Information Security. What the company does, for context: Observe.AI's platform lets businesses deploy specialised AI agents that autonomously handle customer conversations, support frontline teams and optimise operations, with each agent built for a specific role. Location and working pattern: Bengaluru. Office days are not stated. Honest fit guidance: the phrase to weigh is from scratch. This is a build the function role rather than a maintain the function role, which suits someone who wants architectural ownership and is comfortable without an existing playbook. If you want mature tooling and established process, this is the opposite of that. The AWS depth is not optional, since the infrastructure being secured is AWS.
What the posting requires: - 10+ years of experience working on enterprise data lakes and warehouses. - 5+ years of Spark and Python experience. - 5+ years of direct hands on experience with AWS or GCP. - Thorough AI knowledge, particularly with codegen tools and agentic frameworks. - Hive, Iceberg, Glue or other technologies that expose big data as tables. - Familiarity with big data file types such as Parquet, Avro and JSON. Nice to have: - Exposure to real time or streaming data technologies. What the work actually looks like: - Guide the data engineering team on building high performance ETL pipelines using Spark and other big data technologies. - Help design the architecture of the internal data platform to support a robust medallion architecture. - Provide thought leadership on achieving infrastructure cost savings on cloud hyperscalers. - Design and build AI agents that automate common development and support tasks the team performs. - Work with Security and Compliance teams so datasets carry appropriate permissions and regulatory controls. - Work with the Data Platform and Governance sibling teams to keep data scalable, consumable and discoverable. The ramp the employer publishes: - In 3 months: a thorough understanding of the architecture of MongoDB's internal data and AI ecosystem. - In 6 months: ownership of the delivery of a large project from scoping and design through to delivery. - In 12 months: having designed new features, led development work, and become a go to expert on parts of the system. Location and working pattern: the posting states MongoDB is looking for candidates based in Gurgaon for its hybrid working model. Honest fit guidance: at 10 years plus this is a technical leadership seat without being a management one, and the AI agent building brief is a genuine part of the job rather than a bolt on. If your data engineering experience is deep but you have not touched agentic frameworks or codegen tooling, that gap is stated explicitly in the requirements and is worth closing before applying.
What the posting requires: - 10+ years of overall industry experience, with 6+ years in backend, services and distributed systems in Go and/or Python, covering services, APIs and data pipelines you have built and operated in production. - Experience with telemetry, event or data pipelines and the storage and query systems behind them. - Expertise with Kubernetes and AWS for deploying, scaling and operating production services. - Understanding of REST, HTTPS and TLS, and designing and shipping secure APIs. - Fluency with agentic coding systems and genuine curiosity about agent harnesses such as Claude Code, Pi and Codex. The posting notes it is a bonus if you have instrumented one. - Expertise with data structures and algorithms, and strong communication skills. - A BS in Computer Science or equivalent is required, and an MS or equivalent is preferred. What the work actually looks like: - Build the configuration backend service that manages and delivers configuration to clients. - Build the telemetry pipeline: ingest usage events, run a multi category classifier, aggregate performance, security and quality patterns, and feed per user and executive dashboards. - Design and ship reliable, observable, secure services and APIs in Go and Python. - Partner with the ML team that consumes the data, the endpoint team that emits it, and partner organisations on the dashboard front end. What the posting says is in it for you, in its own framing: - You build the measurement engine, and the team's whole strategy of optimising where the data points runs on the pipeline you own. - The backend function is net new, so you set the patterns rather than inherit them. - Netskope's customer footprint gives production signal at a volume most teams never touch. Levelling: the posting says this team hires across all levels and that candidates are individually assessed and levelled by skill and experience, which is why the title spans Staff and Senior Staff. Location and working pattern: Bengaluru. Netskope describes open desk office layouts, so expect an in office team. The number of days is not stated. Application timing: the posting states the application window is expected to close within a set period, so do not sit on it. Honest fit guidance: the 6 years specifically in Go or Python backend and distributed systems is the substantive bar. Green field means less structure and more ambiguity than joining an established platform.
What the posting requires as minimum: - 10+ years of experience building software systems, including both user facing products and internal platforms. The preferred qualifications are described by Stripe as a bonus rather than a requirement, and it says explicitly that if you meet the minimum requirements you are encouraged to apply. What the work actually looks like: - Architect and build scalable, reliable systems underpinning Stripe's sales motion, including APIs and services for deal creation and modelling, multi party approval workflows, contract generation and merchant onboarding at global scale. - Lead the single plane of glass vision for sellers, driving architectural decisions on how first party Stripe components and third party platforms such as Salesforce interoperate, and designing systems that surface the right data and actions at the right time. - Integrate AI and agentic workflows into the selling process, from intelligent deal recommendations and pricing guidance to automated contract workflows and proactive activation nudges. - Partner at a senior level with go to market, finance, legal and product teams, translating business requirements into durable technical solutions. - Raise the technical bar through design and code reviews, and establish engineering standards and best practice. - Drive simplification and platform consolidation, reducing complexity in the go to market systems stack and architecting toward a maintainable, extensible platform. - Mentor and sponsor senior engineers, helping them grow in technical scope and organisational influence. How the team describes its own approach: it treats the selling process as an engineering problem from first principles, implemented as a hybrid architecture of first party custom Stripe components interoperating with third party standard business components. Location and working pattern: Bengaluru, India. Office days are not stated in the posting. Honest fit guidance: internal systems at Stripe still run at payments scale, so do not read internal as small. The specific thing that will distinguish an application is experience owning architecture across a boundary between custom systems and large third party platforms, because that hybrid is the core problem the team exists to solve. Ten years is a real bar here rather than a rounded up preference.
What the posting requires: - 12+ years of professional experience in backend systems or platform engineering. - Experience building platforms, infrastructure or database engineering, especially with MySQL and TiDB. - A track record of building and scaling mission critical platforms supporting high throughput global services. - Experience with schema migration frameworks, CI/CD automation and developer tooling. - A champion of developer experience, creating clear, reliable and user friendly workflows. What the work actually looks like: Schema migration platform: - Architect and maintain automated schema change infrastructure for MySQL and TiDB. - Implement versioning, rollback, validation and auditing for safe, predictable and fast migrations. Scale, reliability and test harness: - Ensure the platform operates across thousands of global databases with zero downtime. - Enhance resilience, observability and recovery. - Build a test harness for migration and deployment validation. Developer experience and CI/CD: - Design intuitive tools and APIs for schema and data change management. - Embed migration workflows into CI/CD pipelines to increase velocity and reduce friction. Schema and data management: - Design infrastructure for safe, large scale schema and data operations such as backfills and purging. - Ensure backfill operations are monitored, retryable, minimally disruptive and automated, maintaining data integrity. Why the role matters, in the employer's framing: the platform underpins Databricks' ability to keep evolving rapidly across thousands of databases and more than 60 mission critical services. Location and working pattern: Bengaluru. Office days are not stated. Compliance note in the posting: the standard Databricks export controlled technology clause applies, under which applying for a US government licence is at the employer's discretion where such access is required. Honest fit guidance: this is one of the most specific postings on today's board, which is good news if it matches you and bad news if it does not. MySQL and TiDB experience at scale is named directly, and schema migration tooling is a real specialism. Twelve years is the highest bar in today's edition alongside Samsara's platform role.
What the posting requires as minimum: - A Bachelor's degree in Computer Science or Engineering, or equivalent practical experience. - 12+ years of experience in software design, development and algorithm related solutions, including time in an architect or leadership role. - Stellar programming and coding fundamentals. - 4+ years of experience building large scale distributed systems. - 4+ years of experience leading cross organisation projects. - Expertise working with web services at massive scale deployed on cloud providers such as AWS, GCP or Azure. What an ideal candidate also has, per the posting: - 15+ years of relevant industry experience in software development. - Enjoyment of leading and mentoring other engineers. What the work actually looks like: - Drive technology choices, implement services and establish architectural patterns with broad and lasting impact on Samsara's platform. - Identify opportunities and initiate strategic conversations that influence the direction of platform technology and engineering culture. - Architect, design and develop software that enables Samsara to operate at scale. - Lead teams delivering products and capabilities that contribute to Samsara's products and revenue. - Solve the hardest technical problems and enable products to reach market quickly with high quality. - Keep a platform first approach while collaborating with infrastructure and product teams. The systems in scope, as named: reporting, automations and enterprise capabilities, plus foundational infrastructure including container orchestration, data storage, real time data ingestion and GraphQL execution. Location and working pattern: this one is stated clearly, which is unusual and useful. The role is hybrid at 3 days per week in the office, at Prestige Tech Park, Kadubeesanahalli, Bengaluru 560103. What Samsara says about the environment: engineers have a rare closeness to the end user, with the opportunity to join customer interviews, work with customer success and product managers, and use metrics to check the work is producing better customer outcomes. Honest fit guidance: 12 years with an architect or leadership component is the real bar, and the ideal candidate note pushes it toward 15. This is a technical leadership seat, so the cross organisation project experience matters as much as the coding depth.
What the posting asks for. GitLab publishes no years of experience figure, so judge yourself against the skills: - Strong software development skills with experience in Ruby on Rails. This is stated as required. - Experience working on distributed applications with large codebases deployed in cloud environments, described as strongly preferred. - A passion and desire to proactively develop security engineering skills. Note that formal security engineering experience is explicitly not a hard requirement for this role. - Comfort working in an all remote environment where results and impact matter above hours worked. - Strong experience with cloud native development on Google Cloud Platform and/or AWS. - Interest in thinking like a hacker and defending against attacks with an automation first mindset. - Interest in handling trust and safety security incidents and collaborating with engineering to harden platform defences. - Experience working on an AI native development team maintaining teams of agents, acting as a code reviewer, and abstracting your role away from writing code in most cases. What the work actually looks like: - Maintain core abuse prevention systems and build new abuse detection rules for evolving platform abuse including spam, AI and token abuse, SEO optimisation and redirects, and other financially motivated campaigns. - Become a core maintainer of the in house abuse platform, a Ruby on Rails monolith, supporting and building new features for it. - Improve and expand agentic AI capabilities in the abuse mitigation tools, including improving multi agent reasoning decision patterns with a target of reducing human in the loop operational load. - Lead collaboration with peer engineering teams to deliver safety improvements to the GitLab product. - Resolve automation gaps and create efficient automated processes. - Create and maintain documentation such as runbooks and procedures. About the team: Trust and Safety is a global team that keeps abusive behaviour off GitLab.com using automation, LLM aided anomaly detection and user behaviour analysis. It works closely with Security Incident Response, Signals Engineering, Threat Intelligence and the Red Team. Location and working pattern: GitLab states that all of its roles are remote, with some carrying location based eligibility requirements its talent acquisition team can clarify. This listing includes India. One more thing worth knowing: GitLab treats AI as a core productivity multiplier and expects team members to use it in daily workflows. Honest fit guidance: this is the clearest route on today's board from software engineering into security engineering, because the posting says so itself. Rails is the non negotiable part.
What the posting asks for. As with GitLab's other listings, no years of experience figure is published: - Strong experience building backend applications with Ruby on Rails in a high scale production environment. - Professional experience with Go for backend or infrastructure oriented services. - A track record of leading architecture across multiple systems and influencing technical direction through strong engineering judgement. - Experience writing clear technical proposals, requests for comments and decision records in an asynchronous, documentation first environment. - A solid security mindset, and comfort working on products where trust, risk reduction and secure defaults are central requirements. - Familiarity with software supply chain security concepts such as build provenance, artifact signing, dependency security or software bills of materials. - Strong teamwork and communication skills across distributed teams and functions. What the work actually looks like: - Define and drive the technical architecture for the supply chain security add on, covering package policy enforcement, provenance generation, artifact signing and malicious package detection. - Lead design and implementation for Supply-chain Levels for Software Artifacts Level 2 and Level 3 capabilities within GitLab CI/CD. - Architect integrations with Sigstore services including Cosign, Fulcio and Rekor, covering signing workflows, verification and trust boundaries. - Design backend services and request paths supporting allow, deny and quarantine package policies with strong performance and reliability expectations. - Review merge requests with a focus on security, architectural consistency, maintainability and test quality. - Mentor backend engineers across experience levels, including participating in hiring. - Partner with Product, Infrastructure, Authentication, Authorization and Security counterparts on cross team decisions. - Contribute to open source and industry conversations, including working groups on software supply chain security. Example projects named: a Dependency Firewall for package policy enforcement across supported registries, and artifact attestation and signing using supply chain security standards and the Sigstore ecosystem. Location and working pattern: GitLab states all of its roles are remote, with some carrying location based eligibility requirements. This listing includes India, and the posting describes the environment as remote, asynchronous and values driven, where written communication and ownership are central. Honest fit guidance: this is a genuine architecture role, so the distinguishing requirement is having defined systems before they were built and written the proposals that got others to agree. Rails at high scale plus real Go experience is the technical floor, and supply chain security familiarity is what will separate applications.
What the posting asks for. GitLab publishes no years of experience figure: - Experience owning product or platform systems end to end across multiple engineering and product teams at the staff level. - Strong fullstack technical skills with proficiency in Go, Ruby and Node. - Depth in at least one of: reporting and metrics platforms, graph data systems, or data access and warehouse integrations including Snowflake, Databricks or BigQuery. - Hands on experience building production data ingestion, systems integrations or data access capabilities. - Experience operating multi tenant systems across both SaaS and self managed environments. - Strong judgement in ambiguity, with the ability to make trade offs, create clarity and move early stage work forward. - Clear written communication, including architecture proposals and design records that help distributed teams progress asynchronously. - A practical and proactive approach to collaboration. The posting welcomes transferable experience from adjacent platform, data or product engineering backgrounds. What the work actually looks like: - Architect how GitLab and third party data is ingested, modelled and synchronised into the Knowledge Graph as a near real time graph of the development ecosystem. - Coordinate integration with external systems such as Jira, observability tools, Zendesk and ServiceNow to add business context. - Design the Data Marketplace so customers can consume GitLab data through Snowflake, Databricks and BigQuery without engineering handoffs. - Publish GitLab observability data as OpenTelemetry and support the APIs used for data access. - Define operational readiness for the systems your team ships across GitLab.com, Dedicated and Self Managed deployments. - Translate ambiguous product problems into practical technical plans and iterative roadmaps with Product, Design and the graph backend team. - Resolve cross team coordination with Graph Backend, AI Platform and Infrastructure. - Mentor senior and intermediate engineers through design reviews, pairing and code review. About the team: Data Products covers Software Engineering Intelligence, dashboard and reporting frameworks, external data access and output, and data ingestion across areas such as DORA metrics, value stream reporting, AI impact, software delivery trends, and security and quality metrics. Location and working pattern: all GitLab roles are remote, with some carrying location based eligibility requirements. This listing includes India. Honest fit guidance: the 0 to 1 framing is the main thing to weigh. If you want a defined roadmap this is the wrong role, and if you want to make the early calls it is unusually attractive. The multi tenant across SaaS and self managed requirement is the technical detail most candidates underestimate.
What the posting lists as must haves. GitLab publishes no years of experience figure, though it does specify senior level: - India based and authorised to work in India, specifically Bangalore, Mumbai or Delhi. - Senior level technical pre-sales, solutions architect or sales engineering experience, able to guide stakeholders through solution design and evaluation. - Proficiency across the end to end software development lifecycle, modern DevSecOps practices and CI/CD workflows, with hands on experience with GitLab or a comparable source control, CI/CD or DevSecOps platform, and the ability to map platform capabilities to customer use cases. - Demonstrated experience working with or in leadership roles inside India based global system integrators, either partner facing or on the delivery and practice side. The posting itself calls this the line that makes it a GSI hire rather than a generic solutions architect one. - Channel, cloud and partner ecosystem fluency: understanding partner sourced motion, deal registration, co-sell and services led go to market, rather than a direct sales only background. - Ability to communicate credibly from practitioner to executive, and to own a technical activation plan as the directly responsible individual. - Willingness to use AI as a core productivity multiplier in daily workflow. Nice to haves: - An existing network inside one or more of the named global system integrators. - Experience standing up partner delivery practices, enablement tracks or certification programmes. - Cloud marketplace or hyperscaler co-sell familiarity with AWS or GCP. - Depth in GitLab, AI development, Kubernetes, infrastructure as code, or application security including SAST and DAST. - Coverage value beyond India, such as APAC GSI delivery hubs. What the work actually looks like: - Work with Ecosystem Sales Managers and partner sales leaders on partner activation plans that drive partner sourced pipeline and GitLab adoption. - Own the technical side of partner activation, building and delivering demos, reference architectures and workshops. - Serve as the directly responsible individual on partner technical activation plans, identifying and addressing technical risks and gaps. - Build relationships with technical and business stakeholders at partners so they move from awareness to leading deal registrations and solution development. - Act as partner advocate internally, sharing field feedback with Product, Engineering, Sales, Marketing and Partner Enablement. Location and working pattern: remote, with the posting requiring you to be India based in Bangalore, Mumbai or Delhi. Honest fit guidance: the GSI requirement is the gate. Strong solutions architecture experience without system integrator exposure will not clear it, because the posting says so directly. If you have worked inside an Indian GSI practice and can hold a technical room, this is a rare remote fit.
What the posting requires. Twilio publishes no years of experience figure here, so measure yourself against the skills: - A Bachelor's or Master's degree in Computer Science, Engineering or a related field. - Hands on experience with high scale messaging and streaming systems and processing engines, at several thousand events per second. - Excellent high level service design skills: modelling interfaces and internals in a properly modular, composable and extensible way. - Expert programming experience in Go or a similar object oriented language. - Demonstrated experience identifying, prototyping and deploying GenAI or LLM solutions to solve real world engineering or data processing challenges. - Technical depth in distributed systems, high scale ingestion and cloud native architecture. - Excellent communication, problem solving and operational excellence skills. Desired rather than required: - Proficiency with datastores, distributed caching and container technologies such as Docker and Kubernetes. - Experience with modern CI/CD pipelines and observability tools such as Datadog, Grafana and Prometheus. - Familiarity with AI and ML technologies. - Experience managing and operating AWS infrastructure. - Experience working in a geographically distributed team. What the work actually looks like: - Own and deliver robust, high scale routing experiences for the Twilio Segment data platform and pipelines team. - Architect and operate always available, complex distributed systems in cloud environments. - Guide technical decisions, articulating trade offs between cost, performance and reliability. - Translate complex technical strategies into actionable plans for stakeholders including product managers and architects. ⚠️ Location, and this one has a real restriction: the role is remote but based in India **only in Karnataka, Tamil Nadu, Maharashtra, Telangana and Delhi**. If you live outside those five states you are not eligible, which is unusual and easy to miss. The posting also says you may be required to travel occasionally for project or team meetings. Benefits stated in the posting: competitive pay, generous time off, parental and wellness leave, healthcare and a retirement savings programme, varying by location. Honest fit guidance: Twilio says it values non traditional career paths and encourages anyone meeting the required qualifications to apply. That said, Principal at Twilio is a senior individual contributor level and the scale described, several hundred thousand data points per second, is the real context. The posting also notes Twilio uses AI in its hiring process, with every hiring decision made by a person.
Added July 25, 2026
What the posting requires: - 2 to 4 years of relevant professional experience. The overview line says 2+ years, and the requirements line says 2 to 4, so treat the low end as the real entry point. - Proven success in a fast paced production support environment. - Strong scripting knowledge in Python, Perl or shell. This is stated as required, not preferred. - Good MySQL exposure, including the ability to write and understand complex SQL joins. - Experience in any programming language. C++, Java or Ruby on Rails are called out as a strong plus. - Familiarity with on call tracking systems and production monitoring solutions. - Demonstrated written and verbal communication skill, with a track record of responding to and resolving customer issues in writing. - Strong analytical and problem solving skills, and the ability to work across functional teams. What the work actually looks like day to day: - Diagnose, troubleshoot and fix production software issues. - Build and own monitoring for both production and non production environments and applications. - Develop smaller complexity features and enhancements inside existing stable components. - Adapt installers, shell scripts and Perl scripts to automate manual tasks. - Keep an ongoing record of problem analysis and resolution in an on call tracking system. - Pass user feedback to engineering and product teams. Location and working pattern: Pune. This is a full time PhonePe role, and the posting notes that the listed employee benefits apply to full time employees only, not interns or contractors. Benefits stated in the posting: medical, critical illness, accidental and life insurance, an employee assistance programme with an onsite medical centre, maternity and paternity benefits, adoption and day care support, relocation and transfer support, PF, gratuity, NPS and leave encashment, plus higher education assistance and a car lease scheme. Honest fit guidance: apply if you have spent two or more years close to production systems and enjoy on call, root cause work and automation. The role explicitly sits between technical operations and business requirements, so if you want to build product features full time this is not it. No interview process is published in the posting.
What the posting requires: - A Masters or PhD in Computer Science, Mathematics, Statistics or a related field. This is listed as a qualification, not a preference. - At least two years of demonstrated ML or AI research experience, either in a professional setting or at a reputable academic institution. Academic research counts here, which is unusual and worth noting. - Software engineering experience in Python and C++. - Experience with TensorFlow, Keras or PyTorch is described as highly desirable. - A track record of academic publications is preferred, not required. What the work actually looks like: - Lead research applying machine learning across a wide variety of datasets and trading problems. - Track academic research and bring techniques from other fields into trading problems. - Improve tick by tick order book time series feature sets using current preprocessing methods. - Build and extend deep learning models against a large in house feature pool and compute cluster. - Build a scalable pipeline for producing predictive models across global markets. - Discover new sources of predictive signal, verify they improve existing models, and integrate them into the firm's strategy pipeline. - Work with quant researchers and software developers to move research into production in Python and C++. - Advise the infrastructure team on hardware and software choices for ML research. Location and working pattern: Gurugram. The posting describes cubicle free offices and a non hierarchical culture, which implies an in office team, though it does not state a fixed number of office days. Benefits stated in the posting: competitive compensation, an annual international team outing, fully covered commuting expenses, health insurance, catered breakfast and lunch, gym and sports club memberships, and four weeks of annual leave in addition to market holidays. Honest fit guidance: this is a research seat at a proprietary trading firm, so the work is model quality and signal discovery rather than product engineering. If you have a strong research record and two years of serious ML work, the low year count will not hold you back here. If you do not have a Masters or PhD, this specific posting is not the one to spend an application on. No interview process is published.
What the posting requires: - 3+ years with Apex, Lightning Web Components, SOQL and JavaScript, working in Agile practices. - Advanced flow development. - API integrations across ETL, marketing tools, ERP and analytics. - Data architecture support, performance optimisation and technical debt reduction. - Deployment and CI/CD support, plus security and scalability improvements. - Technical design collaboration with a System Architect, and the ability to break technical requirements into independent features. - Comprehensive debugging and troubleshooting experience in Salesforce, including spotting the common blind spots and bugs. - Experience working with and optimising millions of rows of data. - Proficiency writing unit tests with assertions for core functionality. Nice to have, listed as desired: - AgentForce, Einstein and other AI tools. - SQL, Python, Data Cloud and Snowflake. - Familiarity with a pay as you go business model. - Developing and deploying through Heroku. What the work actually looks like: - Evolve a Salesforce data model that is scalable, reportable and intuitive for end users. - Build custom functionality with SOQL APIs, Apex controllers, Apex web services and Apex callouts. - Run technical analysis, document integration requirements, and work with architects and stakeholders on integration design. - Review and assure quality on all code entering the codebase. Location and working pattern: remote, based in India. The posting states the role may require occasional travel for in person project or team meetings. Twilio describes itself as remote first. Benefits stated in the posting: competitive pay, generous time off, parental and wellness leave, healthcare and a retirement savings programme, with offerings varying by location. Honest fit guidance: Twilio says openly that it values non traditional career paths and encourages people who meet the required qualifications to apply. The required list is Salesforce heavy, so this is a strong fit for a Salesforce developer with three years in and a weak fit for a general backend engineer. The posting also notes Twilio uses AI in its hiring process, with hiring decisions made by people. No interview stages are published.
What the posting requires: - 3+ years of experience in Chromium environments. This is the stated requirement despite the Sr. Staff title. - Strong C++ design and software implementation skills. - Excellent debugging, memory profiling and performance testing skills. - Experience programming multi threaded solutions, with knowledge of synchronisation techniques. - Good understanding of memory management and runtime optimisation. - Experience developing complex products with many components. - The ability to coach and mentor, and to support the growth of team members. - Strong verbal and written communication. - BSCS or equivalent required. MSCS or equivalent strongly preferred. Nice to have: - Unit testing knowledge, with the posting noting that being a proponent of test driven development is a big plus. What the work actually looks like: - Modify and enhance the Chromium engine to support new Netskope Enterprise Browser features. - Apply advanced data structures and algorithms in C++. - Research optimisation algorithms and improve browser performance. - Work on distributed systems problems around scalability, high availability, containerisation and analytics, using technologies including gRPC. Levelling, which matters here: the posting says this team is hiring across all levels and that candidates are individually assessed and levelled by skill and experience. So the Sr. Staff in the title describes the top of the range, not the entry bar. Location and working pattern: Bengaluru. Netskope describes open desk office layouts and large meeting spaces, so expect an in office team. The number of office days is not stated. Application timing: the posting states the application window is expected to close within 50 days of listing, so this one has a real deadline attached. Honest fit guidance: browser and Chromium work is a narrow specialism. If you have three years inside Chromium or a comparable large C++ codebase, do not be put off by the Sr. Staff title. If your C++ is not current, the rest of the list will not carry you.
What the posting requires as mandatory: - 3 to 5 years of experience, stated as the range for the role. - Linux or Android, with multimedia experience: camera work and GStreamer video or audio pipelines, or equivalent exposure to another streaming framework. - Ability to develop software in C and C++. - Hands on experience designing and implementing software modules on embedded systems. - Good spoken and written communication, and the ability to adapt quickly in a fast moving environment. Preferred skills: - Prior experience with embedded products and Linux OS concepts. - Linux device drivers and RTOS experience. - GPU work with CUDA, OpenCL or SNPE, and algorithm optimisation. - Use of AI tools in day to day work. What the work actually looks like: - Design and implement multimedia based applications. - Develop the test environments and test cases that validate the features you build. - Troubleshoot and debug complex issues in production environments. - Implement software development best practices across the team. Location and working pattern: the posting states the position is based at HM Tech Park, Whitefield, Bangalore. Some other Netradyne listings state an on site five day model explicitly. This one names the office but does not state the number of days, so confirm it with the recruiter rather than assuming either way. A note on the employer: Netradyne includes a recruitment fraud warning in its postings. Official communication comes only from addresses ending in netradyne.com or us-greenhouse-mail.io, and the company says it never asks for sensitive personal data over text or unsecured channels and never charges candidates a fee. Worth knowing before you reply to anyone claiming to recruit for them. Honest fit guidance: this is device side embedded work, close to the hardware, on a real shipping product. If your background is application or backend development, the multimedia pipeline requirement will be the gap. No interview process is published.
What the posting requires: - A Bachelor's or Master's degree in Computer Science or Electronics. - 3 to 6 years of experience in system software development on Linux. - Strong C and C++ programming skills. - Solid understanding of Linux internals: process and thread model, scheduling, memory management and IPC. - Experience with IPC mechanisms including message queues, shared memory, semaphores and DBus. - Familiarity with systemd, udev, init scripts and service management on Linux. - Proficiency in multithreading and synchronisation concepts. - Experience with build systems such as CMake, Make or Yocto. Preferred and bonus skills: - Embedded Linux, socket programming, video streaming and Bluetooth programming. - Hands on use of GDB, Valgrind, strace and perf. - Scripting in Bash or Python. - Exposure to security frameworks and hardening for Linux based systems. - Familiarity with Docker and Kubernetes. - Contributions to open source Linux projects. What the work actually looks like: - Design and implement middleware components and services on Linux based platforms. - Develop and optimise IPC mechanisms. - Work on system daemons, service orchestration and resource management modules. - Collaborate with hardware, firmware and application layer teams. - Perform code reviews, unit testing, integration testing and performance tuning. - Debug and resolve system issues across middleware and lower layers. - Contribute to system architecture and design discussions. Location and working pattern: Bangalore. This posting does not state the number of office days, unlike some other Netradyne listings which specify a five day on site model, so ask. A note on the employer: as with Netradyne's other listings, the posting carries a recruitment fraud warning. Official mail comes only from netradyne.com or us-greenhouse-mail.io addresses, and the company never charges candidates a fee. Honest fit guidance: this is a genuine systems role. If you have written daemons, debugged IPC and worked in a Yocto build, three years is enough to be taken seriously here. Application developers who have not worked below the framework layer will struggle against the required list. No interview process is published.
What the posting requires: - Excellent written and spoken English. The posting calls this non negotiable, because you present architecture to customer CTOs, write documents that hold up in audit, and defend decisions in the room. - Production agentic AI systems you have actually shipped on AWS. The posting calls this the primary qualification and says to be ready to walk through what you shipped, the decisions you made and what broke. Proof of concepts and notebooks are explicitly not enough. - Deep understanding of agentic architecture, including single agent versus multi agent systems, supervisor and orchestrator patterns, hierarchical topologies and planner and executor separation. - Orchestration experience with LangGraph, Strands Agents, CrewAI or equivalent. - Memory design: short term working memory and long term episodic and semantic stores, with vector and graph backed retrieval, and the production trade offs of each. - Reflection and self correction patterns: critique loops, self evaluation, retry with feedback, and evaluation harnesses that catch failures before customers do. - Tool use and function calling: schema design, tool selection reliability, error handling and agent to agent composition. - RAG and retrieval pipelines: chunking, embedding, hybrid retrieval, reranking and grounding in customer data. - Strong AWS production experience with Amazon Bedrock and AWS AI services, plus core services such as Lambda, API Gateway, DynamoDB, RDS or Aurora, Glue, EMR, Redshift and Kinesis. - Solid software engineering fundamentals in Python and TypeScript, with CI/CD, infrastructure as code and test driven discipline. - Roughly 3 to 10 years in engineering roles, with agentic AI or GenAI as your current day job. Nice to have: - Experience with data or application modernisation such as database migration, legacy refactoring or data platform builds. - Delivery experience in financial services, healthcare and life sciences, internet and software, manufacturing, or telco, media, entertainment, gaming and sports. - Model tuning and fine tuning. What the work actually looks like: - Deliver production agentic AI systems and AWS modernisation engagements on committed dates. - Convert existing products and business processes into agents, exposing functionality as callable tools or replacing form and click interfaces with intent driven ones. - Embed with customer engineering teams, run architecture sessions and align stakeholders from VP Engineering to CTO. - Make agent decisions traceable and defensible so outputs survive internal audit and regulators, including HIPAA, PCI DSS and finance grade governance where the vertical demands it. Location and working pattern: Mumbai, with the forward deployed model meaning you embed with customer teams. Honest fit guidance: the deciding factor is whether you have shipped agentic systems into production, not how many years you have. The posting says so explicitly. If your agentic AI experience is demos, this application will not clear the first filter.
What the posting requires: - 3+ years working on ML systems. - Solid PyTorch and ONNX export experience, including the awkward parts: dynamic shapes, control flow and custom ops. The posting names these specifically. - Quantisation in production on at least one real model. - Comfort with at least two of ONNX Runtime, TensorRT, CoreML, OpenVINO, QNN and LiteRT. - Profiling fluency on at least one platform. Nice to have: - Custom op authoring in any runtime. What the work actually looks like: - Own one or two model and chipset pairs end to end, taking each from research handoff to a production ready artifact. - Quantise, validate accuracy, benchmark and document. - Author the deployment workbook for each pair you own. - Embed part time with the consuming app team during integration, debugging performance and accuracy issues with them. - Maintain and extend the team's benchmark harness. Target hardware named in the posting: Intel xPU, ARM xPU, Apple xPU, and Nvidia or AMD GPUs. You are expected to deliver on at least two of these. Location and working pattern: Bengaluru. The posting does not state a hybrid or remote arrangement, so assume in office. What the employer says about the team: a high talent density team, AI first in how it builds and ships, with high ownership from day one and population scale impact as the stated draw. Honest fit guidance: this is a narrow, deep specialism. Three years is enough if those years included real quantisation and profiling work on shipped models. General ML engineering experience without on device deployment will not clear the bar, because the entire role is about the gap between a research checkpoint and a model that runs fast on specific silicon. No interview process is published.
What the posting requires: - 4+ years building ETL pipelines for a data lake or warehouse. - Expertise in Python, Spark, SQL and Airflow. - Experience with data warehousing and engineering concepts, analytical data modelling, data quality validation, monitoring and pipeline reliability practices. - Hive, Iceberg, Glue or other technologies that expose big data as tables. - Familiarity with big data file formats including Parquet, Avro and JSON. - A background building data platforms on cloud, for example AWS, GCP or Azure. Nice to have: - Exposure to real time or streaming data technologies. What the work actually looks like: - Design, build and maintain efficient, scalable ETL and ELT pipelines using Python and Spark across batch, file based and streaming architectures. - Keep data quality, reliability and timeliness in line with established data engineering practice. - Model and store large datasets using modern file and table formats. - Deploy pipelines on cloud infrastructure, mostly AWS with some GCP. - Partner with data analysts and data scientists to deliver the datasets that drive their work. - Work with security and compliance teams so datasets carry the right permissions. - Work with the Data Platform and Governance teams to keep data scalable, consumable and discoverable. The ramp the employer publishes: - In 3 months: you will have built your first ETL pipeline with stakeholders in data analytics and data science. - In 6 months: you will have owned a large project from scoping and design through delivery. - In 12 months: you will have designed new features, led development work and become a go to expert on parts of the system. Location and working pattern: Gurgaon, and the posting states directly that MongoDB is looking for candidates based in Gurgaon for its hybrid working model. So this is hybrid, not remote, and location matters to them. Honest fit guidance: at 4+ years this is the lowest floor of the three MongoDB roles on today's board. The requirement list is squarely data engineering, so a backend engineer without Spark and Airflow depth would be applying against the grain.
What the posting requires: - A BS or higher in Computer Science or a related field. - 5+ years of production level experience in one of Python, Java, Scala, C++ or a similar language. - Experience developing large scale distributed systems from scratch. - Hands on experience developing and operating backend systems. - The ability to contribute across all project phases, from design and development through implementation and ongoing operations, with guidance from senior team members. Nice to have: - Experience in database replication, backup or transaction recovery at a major database vendor such as Microsoft SQL Server, Oracle or IBM. The posting lists this as a plus, and it is the clearest signal of what the team actually values. What the work actually looks like: - Deliver a highly scalable, available and fault tolerant engine processing hundreds of terabytes of data daily across thousands of customers. - Low level systems debugging, performance measurement and optimisation on large production clusters. - Build architecture designs, influence the product roadmap and own new projects. - Help prevent and investigate production issues. - Plan and lead complex technical projects that span several teams. - Break complex problems into solutions, knowns and unknowns, and de risk them through prototyping and validation. Why this team exists: ingesting data into the Lakehouse is described as a strategic investment area, and every Databricks surface including dashboards, notebooks, SQL and AI needs ingestion, so the team works closely with other product teams to embed Connect into those surfaces. Location and working pattern: Bengaluru. Databricks says it is building out its Bengaluru site with new teams, so expect an in office or hybrid arrangement. The number of days is not stated. Compliance note in the posting: where a role requires access to export controlled technology or source code, Databricks says applying for a US government licence is at its discretion and it may decline to proceed on that basis. That clause is in the posting and is worth reading before you invest time. Honest fit guidance: five years plus real distributed systems work is the bar. Database internals experience is what will separate applications here.
What the posting requires: - A BS or higher in Computer Science or a related field. - 5+ years of production level experience in one of Python, Java, Scala, C++ or similar languages. - Experience in software development on large scale distributed systems. - Familiarity with metrics collection, health monitoring and observability tools. What the work actually looks like: - Establish standards for logging, metrics and tracing across the platform. - Work with different teams to identify the metrics engineers need to see how the system and its subcomponents are performing. - Build tooling and infrastructure so components can efficiently emit, aggregate and store metrics for dashboards and alerting. - Contribute to and execute the technical roadmap for scalability, performance and reliability. - Participate in on call rotations and reduce incident response times. - Optimise platform and infrastructure cost by analysing system expenses, improving visibility, enforcing retention policies, streamlining queries and right sizing resources. The scale you would be working at, as stated: millions of virtual machines, terabytes of logs and exabytes of data processed per day, with hardware, network and OS faults treated as expected conditions. Location and working pattern: Bengaluru. The posting mentions Databricks is standing up ten new teams from scratch at this site, which suggests early team formation and the ambiguity that comes with it. Compliance note in the posting: the same export controlled technology clause appears here as on other Databricks roles. Where access to export controlled technology or source code is needed, applying for a US government licence is at the employer's discretion. Honest fit guidance: this is infrastructure engineering, not product. If your background is observability, metrics pipelines or large scale operations, the five year bar is met easily by the right experience. If you have never carried a pager, the on call requirement is stated plainly and is a real part of the job.
What the posting requires: - 5+ years of software engineering experience in full stack development. - Strong experience with Node.js, TypeScript and React.js. - Strong understanding of REST APIs, integration patterns and scalable application design. - Experience with relational and/or NoSQL databases. - Experience with cloud platforms, GCP preferred. - Familiarity with CI/CD pipelines, Git and modern engineering workflows. - Strong problem solving, debugging and collaboration skills. - The ability to work independently and mentor junior engineers. - A Bachelor's degree in Computer Science, Engineering or a related field is preferred rather than required. Nice to have: - Exposure to React Native or mobile application development, listed as preferred. - Exposure to Python for automation, integrations or backend services. - Familiarity with AI and LLM APIs or AI assisted engineering tools, listed as preferred. - Exposure to enterprise platforms or CRM integrated applications. What the work actually looks like: - Develop and enhance scalable backend services in Node.js and TypeScript. - Build responsive, maintainable frontends in React. - Develop and consume REST APIs and integration services, contributing to API first platform initiatives. - Participate in code reviews and technical discussions, and guide junior engineers on development standards. - Support CI/CD pipelines and modern engineering workflows. - Use AI assisted development tools to improve engineering productivity. The posting names GitHub Copilot, Claude, OpenAI and Gemini. Who you report to: a Senior Director, Support Systems and Tools Integration. That reporting line tells you the platform serves internal support and tooling needs as much as external ones. Location and working pattern: Bengaluru, India. The posting does not state office days. Honest fit guidance: a good fit for a full stack engineer with five years who wants senior IC scope with mentoring attached, in a company whose product is physical infrastructure. If you want to work on the EV charging hardware or firmware, this is not that role. ChargePoint states it provides reasonable accommodations throughout the hiring process and gives an email address for accommodation requests.
What the posting requires: - 5 to 8 years of industry experience in data engineering, machine learning engineering or related roles. - A B.Tech or equivalent qualification. - Strong understanding of generative AI system design: prompt engineering, RAG architectures, vector search, and evaluation techniques for LLM applications in production. - Experience with agentic AI patterns, including designing, orchestrating and monitoring autonomous or semi autonomous agents that coordinate tools, data sources and ML services with safety, observability and governance controls. - Experience with workflow orchestration platforms such as Apache Airflow, Prefect or Dagster. - Exposure to real time streaming and messaging systems such as Apache Kafka, Amazon Kinesis and Amazon SQS. - Knowledge of containerisation and orchestration with Docker and Kubernetes or EKS. - Proficiency with at least one Python web framework such as FastAPI, Django or Flask for data and model serving APIs. - Experience with data visualisation and BI tools such as Tableau, Grafana or Plotly Dash. - Familiarity with PyTorch, TensorFlow and Hugging Face Transformers. - Background in large scale data processing and lakehouse or warehousing technologies such as Snowflake, Redshift, Spark or EMR, and Delta Lake. - Experience with rapid prototyping tools such as Streamlit, Gradio or Dash for demonstrating ML solutions to stakeholders. What the work actually looks like: - Design, develop and deploy production ready solutions using generative AI, traditional ML, data science workflows and ETL or ELT pipelines on AWS and hybrid edge to cloud environments. - Build and manage real time and batch streaming pipelines for high volume fleet device data. - Implement MLOps practice: CI/CD for training, automated testing, model versioning, continuous monitoring and orchestration. - Champion data quality and governance with data contracts, validation and SLA monitoring. - Collaborate with product, data science, ML engineering and operations to put AI solutions into customer facing products. Location and working pattern: Bangalore. This posting does not state the number of office days. A note on the employer: Netradyne postings carry a recruitment fraud warning. Official communication comes only from netradyne.com or us-greenhouse-mail.io addresses, and the company never asks candidates for fees or sensitive data over unsecured channels. Honest fit guidance: the Staff title sits on a 5 to 8 year range, so treat it as a senior individual contributor role rather than a principal one. The generative AI and agentic requirements are listed as mandatory, not preferred, which is a meaningful filter.
What the posting requires: - 5 to 8 years of experience building scalable, highly critical distributed systems. The posting frames this as the candidate persona. - A B.Tech in Computer Science or equivalent from a reputed college. This is stated in the posting. - Strong object oriented design skills, the ability to apply design patterns, and the ability to design intuitive modules and class level interfaces. - Experience with highly concurrent multithreaded applications, with attention to system performance and throughput. - Good understanding of system performance trade offs, load balancing and engineering for high availability. - Excellent programming skills in Java, Python or another popular language. - Strong problem solving and debugging skills. - Good understanding of data structures and algorithms and their space and time complexity. What the work actually looks like: - Work on highly maintainable and efficient components and systems. - Act as a pod lead, driving features across multiple sprints. - Design, scope and implement independently. - Identify and resolve performance and scalability issues in an increasingly complex enterprise product. - Improve the overall quality of the code structure and the product. - Maintain both code and non code documentation for the components you own. About the product you would be working on: Hevo Pipeline is a no code platform that connects a company's data sources to give a unified view of the business, with integrations across databases, SaaS applications, advertising channels and more. The stated mission is to make the technology simple enough that people without deep technical skills can solve their own data problems. Location and working pattern: Bengaluru. The posting does not state office days. Honest fit guidance: pod lead is a technical leadership role over a feature stream, so expect ownership and mentoring without the people management overhead. The degree requirement from a reputed college is stated explicitly, which is worth knowing before applying if your background is non traditional. No interview process is published.
What the posting requires: - 6+ years of professional software engineering experience. - Deep experience with at least one modern programming language, with Python, Go and Rust named. - Strong technical judgement and the ability to independently solve complex engineering problems. - Excellent communication and comfort collaborating across teams and disciplines. - Comfort with modern infrastructure and delivery systems including containerised applications, Kubernetes and CI/CD tooling such as Drone.io. - A collaborative, detail oriented approach and an interest in building reliable, usable software. Nice to have, listed as a bonus round: - Experience building and maintaining full stack applications, from frontend UIs through backend API handlers to database migrations. - Experience designing systems or services used by other engineers or teams. - Knowledge of Next.js, FastAPI or React. What the work actually looks like: - Own the implementation and long term maintenance of internal tools and platforms. - Lead technical design discussions and contribute to architectural decisions. - Write high quality maintainable code and set an engineering example for a new team. - Identify and proactively address technical debt, reliability risks and scalability concerns. - Work with engineers, product partners and other stakeholders to prioritise and deliver high impact work. The ramp the employer publishes: - In 3 months: strong ownership of one or more internal systems and a meaningful contribution to ongoing initiatives, plus independently delivered improvements that reduce manual effort or operational friction. - In 6 months: technical improvements or new tooling that measurably improve internal engineering efficiency, reliability or velocity. Location and working pattern: the posting states MongoDB wants candidates based in Gurugram for its hybrid working model. Hybrid, not remote. Honest fit guidance: internal tooling work is often undersold, and this one comes with unusual scope because the team is being built from scratch. If you like owning systems other engineers depend on and you have six years behind you, it is a strong fit. If you want to work on the MongoDB database itself, this is a different part of the company.
What the posting requires: - 6+ years of hands on DevOps experience, with strong expertise designing and managing cloud infrastructure. - Strong experience in VMware to AWS migration projects or large scale infrastructure migrations. - 4+ years of Terraform and CloudFormation for infrastructure as code. - 4+ years in configuration management, systems engineering and managing production grade infrastructure. - A solid Linux and/or Windows administration background. - Deep understanding of AWS services including VPC, EC2, IAM, EKS, ECS, RDS, S3, Backup and CloudWatch. - Production experience with Kubernetes on EKS, ECS and Docker. - Hands on experience designing high availability, disaster recovery, security and backup strategies. - Experience with Landing Zone setup, multi account strategy and AWS governance frameworks. - Proficiency in Git, including branching and merging strategy. - Experience with CI/CD pipelines, automation and operational tooling. Nice to have: - Experience across multiple clouds, AWS plus Azure or GCP. - AWS certifications such as Solutions Architect Associate or Professional, or DevOps Engineer Professional. - Exposure to data platforms such as Amazon EMR, Redshift, Lake Formation and SageMaker. - Experience designing cloud architectures at an L3 or architect level. What the work actually looks like: - Lead infrastructure design and implementation for a large scale VMware to AWS migration, from discovery through production cutover. - Architect secure, scalable, highly available AWS environments including Landing Zones built to AWS best practice. - Design and implement containerised platforms on Amazon EKS. - Define and enforce practice across security, backups, HA, DR, monitoring and operations. - Enable configuration management with Ansible, Chef or similar. - Build CI/CD pipelines and own the build and release lifecycle for customer applications. - Provide L3 support for complex infrastructure and platform issues. - Retire legacy infrastructure and land cloud native architecture in its place. - Mentor engineers and contribute to talent evaluation. The delivery model, stated plainly: senior engineers embed with the customer team and personally carry the delivery commitment against fixed dates, with Mactores absorbing overage cost for delays inside its control. The company describes its agent platform as absorbing the discovery and dependency mapping grind so engineers own the judgement calls. Location and working pattern: Mumbai, embedded with customer teams. Honest fit guidance: this is consulting delivery work with a hard commitment attached, not a platform team seat. If prior migration experience is what you want to build on, the posting is direct that the goal is retired VMware clusters rather than revised project plans.
What the posting requires: - 7+ years building production backend systems at scale. - Strong Go in production: designed, built and operated Go services under real load. - Comfort in Python, since you work in both languages through the rewrite and FastAPI is the current foundation. - A track record designing and operating high scale, low latency, multi tenant distributed systems. - Hands on experience with real time and streaming systems: WebSockets, long lived connections and backpressure. - Strong PostgreSQL and Redis fundamentals covering schema design, query performance and caching strategy. - Comfort running services on Kubernetes in production. - Senior individual contributor judgement: when to build versus buy, optimise versus ship, abstract versus inline, and how to bring others with you. Nice to have: - Experience serving LLM, ASR, TTS or vision models in production. - Background in audio processing with pyav, FFmpeg, codec and sample rate work, or VAD. - Experience building metering, billing or wallet and payments infrastructure. - Time at an early or growth stage startup. What the work actually looks like: - Own the end to end design and evolution of the platform, from the moment a request hits the edge to the response going back out. - Lead the Python to Go rewrite: architecture, patterns and migration without losing reliability. - Audio pipeline engineering: TTS chunking around model context limits, sample rate adjustment, format encoding, VAD based silence detection for ASR. - Vision pipelines: orchestrating OCR, layout detection and VLM harnesses for structured data extraction. - Streaming infrastructure: WebSocket connections, queue based batch processing, backpressure and low latency model invocation. - The commercial layer: metering, billing, prepaid wallet management and rate limiting. - Observability across logging, metrics and tracing, and the integration test harness that lets the team ship without breaking customer APIs. - Partner with the Inference and MLOps teams and mentor them on production engineering. How the team works: design first and documentation first, with RFCs before code, decisions written down, and an explicit goal of no tribal knowledge. Location and working pattern: Bengaluru. No remote or hybrid arrangement is stated. Honest fit guidance: this is a senior IC ownership role, and the Go requirement is not negotiable given the rewrite sits at the centre of the job. Python only backend engineers would be applying against the primary ask.
What the posting requires as minimum: - 8+ years of experience designing, implementing and operating large scale, high performance APIs and services. - Experience implementing server side APIs in dynamic languages such as Ruby, working with document and relational datastores, especially Mongo and MySQL, and comfort exploring unfamiliar datasets. Preferred qualifications, described in the posting as a bonus rather than a requirement: - Experience with large scale financial tracking systems. - Practical knowledge of cloud based services such as gRPC, GraphQL, Docker, Kubernetes and AWS. - Experience in the marketing domain, building products in a marketing technology stack. - Experience with machine learning, recommender systems, product led growth or lifecycle marketing. - Prior experience building distributed systems or microservices architecture. What the work actually looks like: - Design, build and maintain robust, high performance APIs and services. - Keep the infrastructure extensible, scalable and reliable, meeting service level agreements for both external and internal users. - Hide complexity from users behind simple but powerful abstractions. - Partner with engineers, analysts and scientists to build scalable systems and comprehensive interfaces. - Build the APIs powering internal stakeholder facing UI experiences, defining composable data models and durable interfaces. - Debug production issues across services and multiple levels of the stack, with a bias toward long term maintainability. - Improve engineering standards, tooling and processes. Which team you would join: the posting covers several, including Seller Systems (deal modelling and pricing engines, approval and orchestration platforms, CLM and CPQ integrations, onboarding automation, seller analytics and AI assisted tooling) and Finance Engineering (accounting automation, auditing, financial planning and forecasting, business intelligence). Location and working pattern: Bengaluru, India. Office days are not stated in the posting. Honest fit guidance: Stripe says directly that if you meet the minimum requirements you are encouraged to apply and that the preferred list is a bonus, not a requirement. That said, eight years is a real bar, and the specific ask is API and service design at scale. Internal systems work at Stripe still runs at payments scale, so do not read internal as small.
What the posting requires: - 8 to 12 years of software engineering experience with deep frontend expertise. - Expert level proficiency in JavaScript, TypeScript, HTML and CSS. - Extensive experience with React or similar frameworks in large scale applications. - Strong expertise in frontend architecture, design systems and scalable UI development. - Proven experience building and evolving shared component libraries or frontend platforms. - Deep understanding of browser internals, rendering and performance optimisation. - Experience defining and driving frontend standards and best practices across teams. - Demonstrated ability to influence technical direction without direct authority. - Strong ability to translate product and design needs into scalable technical solutions. - Experience with modern frontend tooling, CI/CD pipelines and cloud environments. - Familiarity with observability, monitoring and performance tracking tools. - Experience working on large scale SaaS platforms. Nice to have, listed as good to have: - Leading or contributing to design systems at scale. - Exposure to micro frontend architectures or modular frontend systems. - Familiarity with security considerations in frontend applications. - Experience with AI assisted development tools such as Codex or Cursor. - Background in improving developer experience and platform engineering. - Experience driving frontend modernisation or platform adoption initiatives. What the work actually looks like: - Define and evolve frontend architecture patterns and shared capabilities across product teams. - Lead architecture reviews and guide frontend design decisions across teams. - Drive adoption of shared frontend platforms, frameworks and tooling, and reduce duplicated engineering effort. - Establish engineering standards and decision frameworks for frontend development. - Define and drive standards for performance, accessibility and user experience. - Identify systemic risks such as performance bottlenecks, architectural inconsistency and maintainability problems, and lead cross team efforts to address technical debt. - Mentor senior engineers and act as a technical multiplier across teams. What success looks like, per the posting: within 12 to 18 months successful staff engineers at Ontic are driving initiatives across teams rather than owning a single product area. Location and working pattern: Noida, India. Ontic has the same role open in Pune, so check which location suits you before applying. Office days are not stated. Honest fit guidance: this is a platform and architecture seat for a deep frontend specialist. If your experience is feature delivery in React without shared library or design system ownership, the required list will read as a stretch.
What the posting requires: - 4 to 7 years of experience in a relevant field such as ETL, ELT, data transfer or data warehousing. - Understanding of the database administration and data replication domain. - Understanding of data integration principles and connecting diverse data sources to a warehouse, with in depth knowledge of extracting data from specific sources. - Proficiency in SQL, described in the posting as vital for querying and manipulating data. - Cloud platform familiarity with AWS, GCP or Azure, described as essential since Hevo often pairs with them. - Knowledge of databases including PostgreSQL, MySQL, SQL Server and Oracle, described as crucial. - Experience with API integration and JSON or XML data formats, described as helpful. - Basic proficiency in data transformation tools or languages such as Python, or warehouse specific tools. - Understanding of networking, security and performance concepts. - Understanding of data warehousing concepts including modelling, star and snowflake schemas, normalisation and denormalisation, and optimisation. - Data quality best practices for accurate, reliable integrated data. - A knack for problem solving and debugging. What the work actually looks like: - Manage a book of business and own retention for the customers assigned to you. - Act as a technical consultant and advisor post sales, giving technical and solution guidance. - Own customer onboarding for every new customer assigned to you. - Build and develop data pipelines, and build out of the box solutions when the product hits its limits. - Be the single point of contact for all technical matters on the account. - Drive engagement and adoption, and work with account teams to communicate return on investment. - Lead and organise quarterly business reviews. - Identify new use cases for Hevo products inside the customer base and drive adoption of new features. - Advocate for customers during triage, coordinating with internal teams on high severity cases. - Maintain specialist competency in technologies relevant to Hevo's market through training and certification. Who you report to: the Head of Customer Success. Location and working pattern: Pune, Maharashtra. Office days are not stated. Honest fit guidance: this is a customer facing role that still requires you to build pipelines yourself, so it fits a data engineer who likes customer contact rather than a pure account manager. If you want to write product code all day, the book of business and quarterly business review side of the job will not suit you.
What the posting requires: - 5 to 8 years designing, building and troubleshooting distributed computing applications, with 4+ years delivering production scale Spark, ML or AI solutions in Python, Java or Scala. - 3 to 5 years in customer facing roles such as Technical Account Manager or Solutions Architect, with strong communication and relationship building. - Hands on expertise with data lakes, SQL based databases and cloud data warehousing or ETL tools such as Snowflake, Redshift or BigQuery. - Deep knowledge of Spark core internals, Delta or Iceberg, JVM optimisation and memory management. - Proficiency in AI ecosystems including machine learning, deep learning and generative AI. - Practical experience with AWS, Azure or GCP, plus building and managing CI/CD pipelines, monitoring and alerting. - Proven ability to anticipate, identify and mitigate risk while planning solutions for production problems. - Proven ability to work with cross functional teams and senior leadership. What the work actually looks like: - Advanced troubleshooting and root cause analysis on performance and reliability issues across Spark, SQL, Delta, Streaming and Databricks runtime features, using Spark UI metrics, Mosaic AI Model Service, DAGs and event logs. - Work with R&D and network operations teams to define continuous monitoring that catches performance problems early in customer environments. - Build rapid proofs of concept, then test, deploy and monitor solutions that address customer challenges. - Develop playbooks and maintain a knowledge base of common issues and solutions. - Train customer engineering and business teams on performance tuning, debugging and platform features. - Advocate for customers in business review meetings as their trusted advisor and primary technical contact. - Work onsite with field engineering, sales and product teams during customer engagements and technical presentations. Location and working pattern: Bengaluru. The posting refers to collaborating onsite with field teams during customer engagements, so expect customer site visits as part of the job. Compliance note in the posting: the standard Databricks export controlled technology clause applies, under which applying for a US government licence is at the employer's discretion where such access is required. Honest fit guidance: this role needs both halves. Deep Spark internals knowledge without customer facing experience, or account management skill without the ability to read an event log, will each fall short of the stated requirements. It suits a data engineer who has already spent a few years in front of customers.
What the posting requires: - 6 plus years of experience, stated in the ideal candidate section. - Systems engineering experience covering Linux performance, memory management, I/O tuning, configuration, security, storage, networking, clusters and troubleshooting. - Good understanding of networking concepts and protocols including DNS, TCP/IP and SSL/TLS. - Broad awareness of customer workloads and use cases across performance, availability and scalability. - Experience analysing issues holistically, from the application tier through the database down to the storage. The posting also lists things every candidate must have: - Excellent written and verbal communication. - A genuine desire to help people. - A strong urge to investigate and solve problems, with advanced diagnostic and troubleshooting skills. - The ability to think on your feet, stay calm under pressure and solve problems in real time. - The ability to rapidly learn a wide variety of new technical skills. - Strong teamwork, including the judgement to know when to ask for help. Nice to have: - Comfort with modern AI concepts and proficiency using AI assisted tools to speed up troubleshooting. - Experience with one or more of Java, Python, Ruby, C, C++, C#, JavaScript, Node.js, Go, PHP or Perl. What the work actually looks like: - Work alongside MongoDB's largest customers on complex challenges spanning architecture, performance, recovery and security. - Act as an expert resource on best practice for running MongoDB at scale. - Advocate for customer needs with product management and development teams. - Contribute to internal projects, including software development of support tools for performance, benchmarking and diagnostics. The ramp the employer publishes: - In 3 months: a deep understanding of MongoDB and its ecosystem, and completion of new hire training. - In 6 months: comfortable working frontline with customers, and completion of the MongoDB Certified DBA Associate exam. - In 12 months: building expertise toward a technical experts group, helping peers with advanced diagnostics, and handling technical escalations independently. Location and working pattern: the posting states MongoDB wants candidates based in Bengaluru for its hybrid working model. Honest fit guidance: MongoDB says it considers all candidates with an eye for those who are self taught, curious and multi faceted, which is a real signal for non traditional backgrounds. The systems engineering depth is where applications will be judged, not the years alone.
What the posting requires: - Minimum 7+ years of experience supporting large enterprise customers. - Strong networking background, with extensive and in depth knowledge of TCP/IP, HTTP and HTTPS, cookies and SSL/TLS protocols. - Prior experience supporting network security technologies such as proxies, next generation firewalls, SSL and IPSec, VPNs, DLP and SSO. - Demonstrable experience installing, configuring and administering UNIX, Linux and Windows based systems. Active Directory or LDAP experience is desirable. - Expert troubleshooting across scenarios and systems using common tools such as tcpdump and protocols including TCP/IP, NTP, DNS and DHCP. - Good understanding of web technologies including JSON, XML, SOAP, REST, HTML5, web services and JavaScript. - Hands on experience with traffic analysis tools such as Fiddler and Wireshark. - System and server side experience for troubleshooting. - A B.E., B.Tech or M.Tech degree from a recognised and accredited university. Desired technical skills: - Hands on experience configuring and testing applications for SAML single sign on with various identity providers. WS-Fed and WS-Trust experience is a plus. - Prior experience testing HTTP content rewrite solutions. - Cloud technology including Docker, Kubernetes and open source tooling. - Working experience across Linux, Windows and mobile environments. - Strong familiarity with a scripting language, Python or Java, with Python preferred. - Prior experience mentoring and guiding junior team members. What the work actually looks like: - Own and drive escalated support issues to resolution. - Work critical incident response tasks as required, and general support tickets as required. - Work with support managers, engineering and product management to build and improve processes, procedures and tools. - Drive weekly technical team calls alongside other technical leads. - Share knowledge on new issues with the wider team and field. - Assist and mentor frontline support engineers. Location and working pattern: Bengaluru. Netskope describes open desk offices, so expect an in office team. Office days are not stated. Application timing: the posting states the application window is expected to close within 50 days. Honest fit guidance: this is a deep networking and security support role at the escalation tier. If your support experience is application level rather than packet level, the required list will be the gap.
What the posting requires as minimum qualifications: - 8+ years of experience as a Support Engineer or Senior Support Engineer supporting networking or web security products. - A foundational understanding of AI and ML technologies, and experience leveraging, securing or positioning AI driven solutions within your domain. Zscaler describes itself as an AI forward enterprise and puts this first in the list. - Practical knowledge of networking and security products and enterprise network infrastructure. - Experience troubleshooting network issues with tools such as Ping, Traceroute and MTR. - Hands on experience with SD-WAN, routing protocols including BGP and OSPF, firewall, switching, SSL, secure web gateway and VPN. - Working, hands on knowledge of Ubuntu and Python. Preferred qualifications: - Demonstrated experience with Zscaler products such as ZIA, ZPA and ZDX, or similar cloud security platforms, including TLS and SSL inspection and authentication flows. - Proficiency scripting for automation, efficient troubleshooting and reproducing complex customer environments. What the work actually looks like: - Engage with customers on escalated support issues and critical situations, participating in a 24x7 support operation and a 24x7 on call rotation. - Interface with engineering and assist customers with testing and troubleshooting. - Reproduce customer issues to verify problems, and feed findings back to engineering and operations. - Document incident resolutions in the technical support database when they are not already in the knowledge base. - Understand product direction and customer use cases, and give input on product and code changes across the product cycle. Who you report to: the Senior Manager, Product Support. Location and working pattern: the posting states this is a hybrid role based in the Bangalore or Mohali office. That is one of the few explicit hybrid statements on today's board. Benefits stated in the posting: various health plans, time off for vacation and sick leave, and parental leave. Honest fit guidance: the 24x7 on call rotation is stated up front and should be weighed honestly before applying. If you have eight years in network security support and want escalation level work with direct engineering contact, this is a strong match. Zscaler describes a culture of execution centred on customer obsession, ownership and accountability, with an emphasis on speed.
What the posting requires as minimum: - A B.S. in Computer Science, Engineering (mechanical or electrical) or another technical field. - 8+ years in technical support, solutions engineering or similar roles working directly with complex SaaS products, with at least one area of depth in mobile applications or fleet and telematics workflows. - Proven expertise troubleshooting mobile apps across Android and/or iOS, including device and OS constraints, network behaviour, authentication flows, app configuration and data synchronisation with backend services. - Strong debugging and root cause analysis: decomposing ambiguous multi system issues, identifying the high leverage logs and signals, and driving to a clear root cause and mitigation. - Demonstrated experience working directly with engineering and product: reading Jira tickets and RFCs, validating hypotheses in lower environments, and influencing prioritisation with data and customer impact. - Excellent written and verbal English, with comfort presenting complex technical narratives to engineers and to non technical stakeholders including customer success, sales, customers and leadership, across regions. - A strong ownership mindset and bias for action, including making pragmatic decisions under time pressure. - Demonstrated resourcefulness, creativity and problem solving, and the adaptability to work in a fast paced environment. What the work actually looks like: - Act as primary Level 3 owner for high impact and ambiguous mobile issues across driver, fleet, routing and dispatch flows, asset maintenance, connected workflows and mobile to cloud data mismatches. - Lead structured, hypothesis driven investigations end to end. - Partner with engineering teams across mobile experience, driver management, routing and dispatch, connected workflows, asset maintenance, compliance and product security to assess impact, prioritise fixes and influence roadmaps. - Own customer and stakeholder communication on critical issues, including business impact assessments, periodic updates and post incident summaries suitable for senior audiences in EMEA and globally. - Identify patterns across tickets and incidents and drive product and tooling improvements such as better logging, app state capture and diagnostics. - Maintain internal runbooks, incident playbooks and knowledge base content, reflecting regional nuances such as EMEA regulations and language support. - Mentor and coach Level 2 engineers on troubleshooting depth, documentation quality and escalation criteria. - Analyse device telemetry and fleet level patterns using internal tools. Location and working pattern: Bengaluru. The posting refers to supporting senior audiences in EMEA, so expect some overlap with European hours. Honest fit guidance: this is a senior support engineering role with real technical depth and real writing load. Both matter here: the posting asks as much for clear narratives to executives as for log analysis. If mobile debugging is not one of your strengths, the stated area of depth requirement will be the gap.
What the posting asks for. Note that GitLab does not publish a years of experience figure for this role, so judge yourself against the skills rather than a number: - Experience operating backend services in production, including deployment, monitoring and maintenance in Kubernetes and Helm based environments. - Proficiency in Go for building observable and resilient services, with working knowledge of Ruby as a useful addition. - Hands on practice with infrastructure as code, including Terraform, and managing infrastructure across cloud providers such as Google Cloud Platform, AWS or Microsoft Azure. - Knowledge of database design, operations and troubleshooting, especially PostgreSQL in secure and scalable setups. - Knowledge of secure, scalable and reliable deployment practices, including service scaling and rollout strategies. - Familiarity with observability tools and patterns such as Prometheus and Grafana. What the work actually looks like: - Maintain and evolve the Omnibus GitLab package for reliable, production ready self managed deployments, improving deployment stability and upgrade success rates and reducing escalations. - Develop and improve GitLab Helm Charts so core components integrate cleanly and scale across supported environments. - Enhance the GitLab Environment Toolkit, validated reference architectures and the GitLab Operator for secure, Kubernetes native lifecycle management. - Improve installation, upgrade and operational workflows so self managed customers get a consistent experience. - Partner with Security to address vulnerabilities and deliver secure defaults in the deployment stack. - Build and maintain CI/CD pipelines that validate and test Omnibus, Charts, GET and the Operator. - Work with Distribution Engineers, Site Reliability Engineers, Release Managers and development teams. - Guide architectural direction, mentor backend engineers and contribute to the roadmap for self managed delivery. How the team works: the posting describes a globally distributed, all remote group working asynchronously with SRE, Release, Security and Development teams across regions. Location and working pattern: GitLab states that all of its roles are remote, and that some roles carry specific location based eligibility requirements which its talent acquisition team can clarify. This listing is open to India. That combination, remote backend work open to India, is the single most requested thing by readers of this list. One more thing worth knowing: GitLab states that it treats AI as a core productivity multiplier and expects all team members to incorporate AI into their daily workflows. Honest fit guidance: with no years figure published, the deciding factor is whether you have run backend services in Kubernetes and written Go. Deployment tooling is a specialism, so if you have packaged and shipped software that other people install and operate, that experience counts here more than a year count would.
What the posting asks for. GitLab publishes no years of experience figure on this role, so measure yourself against the skills: - Proven backend engineering experience, including production Ruby on Rails expertise, since Rails is the team's primary language. - Working knowledge of Go, or a clear willingness and ability to ramp up quickly in it. - Solid API design skills, including REST, GraphQL and defining clear internal service boundaries. - Solid PostgreSQL fundamentals including schema design, query optimisation and indexing strategies. - Experience with Redis for caching and distributed coordination patterns. - A security aware engineering mindset. What the work actually looks like: - Design and implement backend features across the add on's supply chain security surface: policy enforcement, artifact signing and verification, provenance attestation APIs and malicious package detection integrations. - Build and improve the package policy evaluation engine, covering rule compilation, request matching, enforcement decisions and performance sensitive execution paths tied to GitLab's Dependency Firewall. - Develop artifact signing and verification workflows using Sigstore and Cosign, including signing key lifecycle management, keyless signing with OpenID Connect, and policy based promotion gates. - Create and evolve the configuration interfaces enterprise security teams use, including backend APIs and the GraphQL surface. - Integrate the add on with GitLab's existing security policy framework, including policy inheritance and policy as code through YAML. - Write and maintain comprehensive RSpec and integration test coverage, and improve test reliability across the team. - Review merge requests with a security first mindset, with substantial decision making scope in partnership with the Staff Backend Engineer. What kind of team this is: the posting describes a founding role on a small team with a high level of responsibility, and says the engineering choices made in API design, testing, performance and security will shape how the product grows. Location and working pattern: GitLab states that all of its roles are remote, with some carrying location based eligibility requirements that its talent acquisition team can clarify. This listing is open to India. The posting also describes GitLab's all remote, asynchronous environment as part of what the role is suited to. One more thing worth knowing: GitLab expects team members to incorporate AI into their daily workflows, stating it treats AI as a core productivity multiplier. Honest fit guidance: the Rails requirement is primary and explicit, so this is a fit for a Rails backend engineer with security interest rather than a security specialist looking to learn Rails. Founding team means less process and more ambiguity than a mature team.
What the posting asks for. As with GitLab's other listings, no years of experience figure is published: - Strong software engineering experience designing and delivering production systems that customers install and operate in their own infrastructure. - Proficiency in Go for large, complex codebases, with familiarity with Ruby on Rails and Rails application architecture as a useful addition. - Hands on production Kubernetes experience, including building and maintaining Operators, designing Helm charts for stateful applications, and working with Custom Resource Definitions, admission controllers and controller patterns. - Knowledge of cloud native systems and tooling such as service mesh, observability stacks, infrastructure as code and automation tools like Terraform or Ansible. - Experience with stateful workloads and databases, including PostgreSQL schema design and migrations, persistent volumes, storage classes and approaches for reducing downtime during upgrades. - Understanding of Linux systems and production operations, including package management, systemd, system level debugging, observability, incident response and on call participation. - The ability to guide through influence: clear technical proposals, documented decisions, mentoring and cross team work. - Interest in open source infrastructure or deployment tooling, or transferable experience from adjacent domains. What the work actually looks like: - Guide the technical vision and architecture for GitLab's cloud native self managed deployments and upgrade workflows. - Establish operational maturity standards, service integration patterns and deployment models. - Design and maintain Kubernetes Operators, Helm charts and upgrade orchestration tooling. - Develop automation and integration frameworks for database migrations, rolling deployments, compatibility checks and rollback paths. - Define database and application lifecycle strategies, including safe PostgreSQL migration approaches. - Work with product management, GitLab.com SRE, GitLab Dedicated and development teams to align deployment patterns with customer needs. - Mentor engineers and enable customer facing teams through design reviews, code reviews, documentation and runbooks. - Drive observability, testing, performance and resilience practice, and contribute to incident response and post incident learning. What the first year looks like, per the posting: helping define the architecture for zero downtime upgrades, strengthening observability and reliability practice, and guiding the next generation of deployment automation for self managed environments. Location and working pattern: all GitLab roles are remote, with some carrying location based eligibility requirements. This listing is open to India. Honest fit guidance: this is the most senior of the four GitLab roles on today's board even though none of them state years. Kubernetes Operator authorship and stateful upgrade experience are the distinguishing requirements, and without them the rest of the list will not carry an application.
What the posting asks for. GitLab publishes no years figure, but the overview describes the target level as Intermediate, which is the clearest levelling signal across GitLab's four listings today: - Professional experience operating production infrastructure on AWS at scale, including EC2, Auto Scaling Groups, IAM and VPC networking. - Strong infrastructure as code experience with Terraform, including writing and refactoring modules used by other teams. - Proficiency in Go for building and debugging infrastructure tooling, or strong experience in another systems language and willingness to work in Go daily. - Practical knowledge of CI/CD systems and job execution: how pipelines schedule work, how ephemeral build environments are provisioned and torn down, and what makes CI workloads reliable. - Experience with observability practice including metrics, dashboards, alerting, logging and SLO based monitoring, using tools such as Prometheus, Grafana and OpenSearch. - Experience with on call rotations and incident management for customer facing systems. - Strong problem solving, excellent written communication, and comfort working asynchronously across the Americas, Europe, Middle East, Africa and Asia Pacific. Nice to have: - Direct GitLab Runner experience. - Familiarity with configuration management such as Ansible. - Container tooling such as Docker. What the work actually looks like: - Design, build and operate AWS infrastructure for Hosted Runners across many single tenant environments, spanning EC2, Auto Scaling Groups, VPC networking, subnets, NAT, network ACLs, PrivateLink, IAM and ECR. - Develop and maintain infrastructure as code in Terraform, contributing to common modules and deployment tooling. - Write Go for runner tooling and autoscaling components, including instance lifecycle plugins, a zero downtime deployment CLI and reusable infrastructure toolkits. - Build and improve the GitLab CI/CD pipelines that orchestrate blue green zero downtime deployments, automated upgrades, QA validation and performance testing. - Define and monitor service level objectives for CI job execution, and build the dashboards, alerts and runbooks behind them. - Participate in an on call rotation, handle incidents affecting customer CI/CD workloads, and automate recurring toil away. - Run performance and scale testing that reflects real customer workloads, and tune autoscaling for cost and reliability. - Write documentation and runbooks so the team can operate runner stacks consistently. Location and working pattern: all GitLab roles are remote, with some carrying location based eligibility requirements. This listing is open to India, and the posting explicitly asks for comfort working asynchronously across many time zones. Honest fit guidance: if you have run AWS infrastructure with Terraform and are willing to work in Go daily, this is the most approachable of GitLab's four openings today. The on call rotation is stated plainly. Do not let the SRE title put you off if your Go is not deep yet, because the posting accepts strong experience in another systems language plus willingness to work in Go.
Added July 24, 2026
What the posting asks for: - Professional experience with Ruby on Rails. - A background in site reliability or observability engineering: monitoring, alerting, SLOs, SLIs, runbooks, incident handling, and tools such as Prometheus, Grafana and OpenTelemetry. - Experience building anomaly detection, monitoring or risk management tooling. - Exposure to reporting data stores, especially ClickHouse, and the change data capture and event streaming pipelines that feed them (Siphon, NATS JetStream). - Experience with billing, financial or other business critical systems. - Experience owning a project from concept to production, including proposal, discussion, execution and monitoring. - Clear written communication in English, because the team is remote and largely asynchronous. Counts as a bonus: - Working knowledge of Python for anomaly detection and data work. - Hands on experience with Zuora or Salesforce. The day to day: designing metrics, logs and traces across the Monetization stack, building automated detection for billing and event anomalies and routing those alerts to the right feature team, writing reconciliation and data integrity checks across usage and billing pipelines, defining SLOs and SLIs, writing runbooks, taking part in incident handling, and reviewing other engineers' merge requests. You would report to the Engineering Manager for Observability, Monitoring and Integrations. Experience: GitLab publishes no years figure anywhere in this posting, so we have left it blank rather than guess. What the posting does say is that the role is open at both the Senior Software Engineer and Staff Software Engineer levels, and that GitLab welcomes candidates with varying levels of experience because many successful hires do not meet every requirement. Location: fully remote. GitLab states that all of its roles are remote, though some carry location based eligibility rules, so confirm yours with the recruiter early. Who should apply: a backend engineer who is comfortable in Rails and genuinely enjoys observability work. This is a greenfield team, so you would help set its operating rhythm and quality bar rather than inherit one. If you want a tightly specified ticket queue, this is not that.
What the posting asks for: - Professional experience working with Ruby on Rails. - Experience integrating with third party or enterprise APIs, including billing, CRM or automation platforms. - Strong API design skills: REST, GraphQL, contracts, versioning and backward compatibility. - Familiarity with event driven patterns such as webhooks and message based streaming. - Familiarity with PostgreSQL or a similar relational database, and with data integrity and governance concepts in production. - Systems thinking, and experience owning projects from concept through production. - Ability to communicate clearly in a remote, largely asynchronous environment. Counts as a bonus: - Familiarity with NATS JetStream. - Experience with subscription management or billing systems such as Zuora or Salesforce. The day to day: building and maintaining the integrations between CustomersDot, Monetization services and enterprise applications, defining and evolving API contracts, tracking failure rates and retry success and data integrity incidents, keeping data consistent across integrated financial systems, reviewing merge requests, and working with Product, Finance, IT, Sales and Support to turn cross system needs into reliable integrations. Experience: no years figure is published, so we left it blank rather than invent one. The posting states GitLab is hiring this role at the Software Engineer and Senior Software Engineer levels, and GitLab's standard note applies: they welcome candidates with varying levels of experience and many successful candidates do not meet every requirement. Of the four GitLab roles in today's list this is the one aimed lowest. Location: the posting lists Bangalore, but GitLab is a fully remote company and states that all of its roles are remote, with some carrying location based eligibility rules. Who should apply: a Rails engineer a few years in who wants API and integration depth rather than feature work, and who is comfortable being careful because the data is financial.
What the posting asks for: - Expert knowledge of cloud infrastructure security (AWS, GCP or Azure), container orchestration with Kubernetes, and related infrastructure and data security topics. - Proficiency in multiple programming languages (Go, Python, Ruby) with a track record of shipping production quality security tooling. - Extensive experience with Infrastructure as Code security (Terraform, Ansible, CloudFormation), policy as code and automated compliance. - Hands on experience applying AI to security workflows, with a view on where it creates real leverage. - A track record of leading multi team technical initiatives from an ambiguous problem statement to a measurable outcome, setting direction that peer teams adopt. - Strong written and verbal communication, including explaining security tradeoffs to senior leadership. - Familiarity with security certifications and frameworks: FedRAMP, ISO 27001, SOC 2, PCI DSS. The day to day: setting architectural patterns, reference implementations and foundational security automation; leading security initiatives from problem framing through delivery; running security reviews and threat modelling for complex infrastructure; setting the team's approach to AI assisted security engineering; acting as the authoritative technical voice for Infrastructure Security with stakeholders; and mentoring engineers. GitLab also expects the team to secure GitLab's own infrastructure using GitLab, which they call dogfooding. Experience: no years figure is published anywhere in the posting, so we left it blank. Staff at GitLab is a senior individual contributor level, and the responsibilities listed (multi quarter ambiguous initiatives, setting direction other teams follow) point well above entry level even though no number is given. Location: remote, and open to India, Israel, the United Kingdom and the United States. GitLab notes some roles carry location based eligibility rules. Who should apply: an experienced infrastructure or cloud security engineer who wants scope over a platform rather than a queue of findings, and who is comfortable writing the tooling instead of only reviewing it. This is a leadership role without direct reports.
What the posting asks for: - A proven track record of delivering actionable intelligence that measurably improved an organisation's security. - Experience working with a Threat Intelligence Platform and managing ingested and exported threat feeds. - Experience researching adversaries using OSINT and structured analytical techniques. - The ability to automate tasks by writing scripts or programs, preferably in Python. - Excellent written and verbal communication, with the ability to make complex topics clear. Counts as a bonus: - Experience reverse engineering malware, particularly macOS and Linux malware and malware delivered through code repositories. - Public blogs or open source work related to threat intelligence. The day to day: monitoring the threat landscape and raising ad hoc Flash Reports, administering the Threat Intelligence Platform and extending the open source, proprietary and internal collection pipeline, supporting incident response through malware analysis and threat actor tracking, collaborating on Purple Team Flash Operations where an emerging threat becomes a live exercise, building relationships with industry peers to share intelligence, and writing code and automation to make the team more efficient. Experience: GitLab publishes no years figure, so we left it blank. The posting describes the person as a seasoned threat intelligence engineer and the level is Senior, but no number is given and we will not invent one. Location: remote, open to Canada, India and the United States. Note the manager sits in Australia, so expect some meetings shifted towards Asia Pacific hours rather than a purely India schedule. Team context worth reading carefully: you would be the only dedicated person on this team, supported by Security Operations engineers who spend part of their time on threat intelligence. That is a lot of autonomy and also a lot of solitude. Security Operations at GitLab also covers SIRT, Trust and Safety, Signal Engineering, Red Team and Security Logging. Who should apply: someone who already does threat intelligence and wants to own a programme end to end rather than be one analyst among many. If you need a senior peer in the same specialism sitting next to you, read the team note again first.
What the posting asks for: - 7+ years of experience building campus or data centre network infrastructure, AWS cloud services and networking. - 5+ years with Cisco LAN, WAN and WiFi and Palo Alto Networks firewalls. - 3+ years with AWS cloud services and networking. - Advanced knowledge of IEEE 802 standards and core IETF protocols, including the 802.11 suite, TCP/IP, DNS, DHCP, and routing and switching protocols. - Hands on network monitoring knowledge. - Knowledge of network security, enough to implement security policy for compliance. - Client networking on Windows, Mac and Linux. - Experience troubleshooting network problems across different OSI layers. - A university degree in computer science or equivalent experience. Counts as a bonus: - Cisco CCNA or CCNP certification, and AWS certification. - Zscaler Zero Trust Systems experience or certification. - A scripting language with API automation, and Terraform for infrastructure as code. - Knowledge of ITIL, and project management skills. The day to day: building and supporting the global IT network, tracking network assets, reporting performance and availability metrics to IT leadership, working with stakeholder teams on future network needs, prioritising work using the Scaled Agile Framework, building tools to test and roll out new LAN and WAN systems, responding to incidents, and maintaining network design and standards documentation. Experience: the posting states 7+ years for the primary requirement. Read the three requirements together, because they stack: 7+ years overall on network infrastructure, of which 5+ on Cisco and Palo Alto and 3+ on AWS. Location and travel: remote within India, but restricted to Karnataka, Tamil Nadu, Telangana, Maharashtra and Delhi. Roughly 15 percent travel is expected. Who should apply: a network engineer with real data centre and campus experience who wants to stay hands on. Note this is corporate and internal infrastructure, not Twilio's carrier or product network, so it is closer to enterprise IT engineering than to telecom product work.
What the posting asks for: - Twilio product experience. The posting states this as a must, so it is the hard filter on this role. - 5+ years in Technical Support, Product Operations, Technical Account Management or Engineering, focused on complex technical products such as APIs, SaaS or telecommunications. - Experience in the technology industry, including APIs and VOIP, in either a development or a support capacity. Familiarity with customer or consumer trust applications is preferred. - Proven analytical skills using data tools such as Splunk, Datadog, Snowflake, SQL or Tableau to turn customer feedback and support trends into insight. - Excellent communication and influencing skills, since the job is largely persuading engineering to prioritise supportability work. Counts as a bonus: - Project management experience, or experience running programmes and product launches. - Proficiency in Python, Java or Node.js, enough to understand the developer experience. - Knowledge of design thinking or UX principles for spotting friction in customer journeys. The day to day: embedding supportability requirements into the earliest stages of the product development lifecycle by joining design reviews and technical planning with R&D, analysing support data to build business cases, specifying proactive product features such as clearer error messages and diagnostic tools, orchestrating global operations readiness for new features, and translating complex customer use cases into requirements. Experience: the posting states 5+ years, and accepts that experience from four different directions (support, product operations, technical account management or engineering), which makes it more open than the title suggests. Location: remote within India, restricted to Karnataka, Tamil Nadu, Telangana, Maharashtra and Delhi. Who should apply: someone who has done deep technical support or technical account management on an API product, is tired of fixing the same issue repeatedly, and wants to attack the cause upstream instead. Twilio also says openly that it values non traditional career paths for this role. The Twilio product experience requirement is the real gate, so if you have never used Twilio in anger, expect a hard time.
What the posting asks for: - 15+ years of experience designing and scaling distributed systems and platforms. - A demonstrated ability to set technical vision and strategy at enterprise or company wide level. - Expertise in system design, reliability, scalability, security and cost optimisation for large scale architectures. - Experience leading cross functional initiatives and resolving highly complex, ambiguous technical problems. - A proven record of mentoring senior engineering talent and raising organisational standards. - Exceptional written and verbal communication, influence and leadership skills. - A bachelor's degree in computer science, engineering or a related field, or equivalent practical experience. Counts as a bonus: - Cloud native, multi region systems and architecture patterns. - A history of driving engineering standards across multiple business units or product lines. - Experience with observability, platform capabilities and data architecture at scale. - Open source project leadership or significant external technical impact. - Prior experience at a high growth SaaS, communications or platform company. The day to day: setting and communicating long term architectural vision, leading cross product architecture reviews, standardising engineering practices, driving foundational technical investments, solving the hardest platform wide problems, mentoring principal and staff engineers, and partnering with product, engineering and executive leaders on strategic direction. Experience: the posting states 15+ years explicitly. This is genuinely a senior role and the number is not padding. Location and travel: remote within India, restricted to Karnataka, Telangana, Maharashtra, Delhi and Tamil Nadu. Occasional travel for project or team meetings. Who should apply: a principal or staff engineer with well over a decade of distributed systems work who wants architecture scope across an entire company and does not want to move into management to get it. If you are earlier in your career, the other two Twilio roles in today's list sit far lower.
What the posting asks for: - 15+ years with big data technologies such as Apache Spark, Kafka, cloud native services and data lakes, in a customer facing post sales, technical architecture or consulting role. - 6+ years working on big data architectures independently. - 2+ years on AI based implementations including RAG, MCP and context engineering. - Strong experience within the Databricks ecosystem. - Comfortable writing code in either Python or Scala. - Experience across cloud platforms: GCP, AWS or Azure. - Documentation and whiteboarding skills. - Excellent problem solving and critical thinking, turning business problems into reliable technical products. - Strong stakeholder management, working with both technical people and domain experts. The day to day: collaborating on customer big data projects, creating reference architectures and how to guides, building production ready tooling, advising strategic customers on transformational initiatives including third party migrations, providing architecture and design expertise, partnering with Engineering and Customer Support to feed issues back into the product, and running several diverse client projects at once while managing risk and building trust. Experience: the posting states 15+ years as the headline requirement. Read the three numbers as a stack rather than alternatives: 15+ years overall in a customer facing big data role, 6+ years on big data architectures independently, and 2+ years specifically on AI implementations. The AI requirement is the newest and probably the one most people will fail, not the 15. Location: remote within India. This is one of very few remote senior data roles on the board today. Who should apply: a senior data architect or consultant who genuinely likes customer facing delivery. If you want to build product rather than deliver projects, this is the wrong side of Databricks. Note also that the AI expectation is concrete, not decorative: they want RAG and MCP work you have actually shipped.
What the posting asks for: - 5+ years in a data engineering, data science, technical architecture or similar pre sales or consulting role. - 5+ years with big data technologies including Apache Spark, AI, data science, data engineering, Hadoop and Cassandra. - Strong consulting and customer facing experience with external clients across a variety of industry markets. - Coding experience in Python, R, Java, Apache Spark or Scala. - Experience building distributed data systems. - Solutions built on a public cloud: AWS, Azure or GCP. - Availability to travel to customers in your region. Counts as a bonus: - Databricks certification. The day to day: partnering with the sales team and giving technical leadership so customers understand how Databricks solves their problem, helping develop the book of business and define account strategies, consulting on big data architectures, implementing proofs of concept for strategic projects, validating integrations with cloud services and home grown tools, supporting fellow Solutions Architects, and promoting and recruiting contributors for Databricks backed open source projects such as Spark, Delta Lake and MLflow. Experience: the posting states 5+ years, twice, once for the pre sales or consulting side and once for big data technologies. Compare before you apply: Databricks currently has the same job title live in Delhi at 5+, Bengaluru at 8+ and Pune at 12+. The title alone tells you nothing about the bar. Location: hybrid, based in Delhi, with travel to customers in the region. Who should apply: a data engineer or data scientist who enjoys the customer conversation and wants to move into pre sales without waiting until 10 years in. Be clear eyed that this is a commercial role attached to a sales team, with a book of business and account strategy, so it is not a pure engineering job.
What the posting asks for: - 15+ years of experience in a hands on software engineering role. - A bachelor's or master's degree, preferably in computer science, or equivalent experience. - Experience building, leading and architecting production systems or features with broad impact. - Demonstrated technical leadership: leading project teams, setting technical direction and strategy, prototyping to iterate on ideas, and working across Product, Design and Operations. - Strong communication and collaboration with both technical and non technical partners, including driving initiatives across teams, departments and leadership. - A track record of levelling up the people around you. - Proven experience defining product or technical strategy and getting cross functional leaders aligned behind it. The day to day: working with other senior leaders to define long term technical strategy and architecture, establishing technical vision and leading the work to architect and launch reliable and scalable systems, giving a balanced critical view of new and existing technologies, influencing cross functional partners, leading multi team technical initiatives, aligning technical effort with business outcomes, and raising engineering quality through design and code reviews, mentorship and hands on implementation. Experience: the posting states 15+ years in a hands on software engineering role. Airbnb is explicit that this stays hands on, so it is not an architecture role that has drifted away from code. Location: remote and eligible anywhere within India. The role may include occasional work at an Airbnb office or attendance at offsites, agreed with your manager. Remote roles at this level and in payments are uncommon, which is the main reason this one is worth a look. Who should apply: a very experienced engineer who wants payments scale and cross team architectural ownership while staying an individual contributor. If you are below roughly a decade of experience this is not a stretch application, it is the wrong role, and there are lower bands elsewhere in today's list.
What the posting asks for: - A bachelor's or master's degree or equivalent in computer science or a related field. - 2 to 5 years of relevant work experience. - Proficiency in one or more general purpose programming languages: Java, C, C++, Scala, Python or C#. - Rubrik describes its engineers as self starters who manage themselves, which is worth taking at face value in a distributed systems team. Counts as a bonus: - Prior experience with C++ specifically. - Google Cloud Platform, AWS, Azure or other public cloud technologies. - Experience with two or more of: Unix or Linux environments, Windows environments, distributed systems, networking, developing large software systems, file systems, storage systems, hypervisors, databases, or security software development. The day to day: designing, developing, testing, deploying and improving the software; managing your own projects, priorities, deadlines and deliverables; identifying and fixing bottlenecks in the software stack; and diagnosing and resolving problems inside complex customer environments. Experience: the posting states 2 to 5 years, which is the real floor and ceiling. Of everything in today's edition this is the closest thing to a role a recent graduate can grow into, though it is not a fresher posting and we are not going to pretend otherwise. Location: Bengaluru. A note on the link: rubrik.com blocks automated requests, so this posting was verified live through the Greenhouse jobs API rather than by fetching the page. It was published on 23 July 2026 and is open. The link works normally in a browser. Who should apply: someone two to five years in who wants file systems, storage and distributed systems rather than application or web work. If you have C++ and Linux and you have been stuck on CRUD services, this is the kind of role that changes the shape of your career. Expect systems design and debugging to dominate the interview.
What the posting asks for: - 2 to 5 years of experience, stated plainly at the end of the posting. - Python and SQL. The posting marks both as required for this role. - Hands on experience with Windows, Linux or Mac environments. - Knowledge of at least one programming language such as PHP, Java or ASP.Net, and of the Android and iOS platforms. - The ability to diagnose and troubleshoot technical issues and give step by step technical help. - Familiarity with remote desktop applications. - Excellent problem solving and communication skills. - A good grasp of general IT terminology and concepts. The day to day: managing merchant accounts during integration, working with the product and technology teams to understand different product flows, attending meetings and calls with merchants' technical and business teams, understanding a merchant's flow and requirements and proposing a solution, researching and diagnosing integration issues through to resolution, asking targeted questions to find the root of a problem quickly, and automating the recurring problems so they stop coming back. Experience: the posting states 2 to 5 years directly. This is one of the lower bars in today's list and one of only a handful under three years. Location: Bangalore, at PhonePe's office. Benefits worth knowing, since PhonePe lists them in detail for full time employees: medical, critical illness, accident and life insurance; an employee assistance programme and an onsite medical centre; maternity, paternity, adoption and day care support; relocation and transfer support; provident fund, gratuity, NPS and leave encashment; and higher education assistance. Who should apply: someone with two to five years who likes solving other people's integration problems and wants fintech scale on their CV. Be honest with yourself about the customer facing half: a large share of this job is calls with merchants, not heads down coding. If you want pure backend work, PhonePe's engineering roles are a different queue.
What the posting asks for: - Up to 5 years of experience building end to end applications. Read that carefully: it is an upper bound, not a minimum, which is why this role is open to people early in their careers. - A strong understanding of AI and machine learning fundamentals: NLP, LLMs, embeddings and prompt engineering. - Proficiency in Python and working with REST or GraphQL APIs. - Experience with prototyping frameworks such as Flask, FastAPI or Streamlit. - Familiarity with go to market systems such as Salesforce, HubSpot or Marketo, or BI tools such as Tableau or Looker. - Strong problem solving skills and the ability to prototype quickly. Abilities the posting calls out separately: - Turning messy go to market data into usable inputs for AI models. - Mapping AI outputs back into real workflows and processes. - Explaining technical solutions clearly to non technical people. - Balancing fast experimentation against reliability and compliance. The day to day: building internal applications on LLMs and AI APIs such as OpenAI and Anthropic, integrating AI into go to market tools, writing scripts and automations for data enrichment and reporting, rapidly testing new models and APIs and building MVPs, documenting performance and accuracy for each use case, working with Marketing, Sales and BizOps to find their pain points, running demos and training for internal users, and maintaining what you deploy. How success is measured, which the posting states unusually clearly: two or three working AI prototypes that go to market teams actively use, at least two workflows automated or optimised, documentation good enough to make the work transferable, and measurable gains in productivity. Experience: up to 5 years, with no minimum stated anywhere in the posting. Location: Bangalore. Who should apply: anyone from roughly zero to five years who can actually build with LLM APIs and wants a role where shipping a working prototype counts more than pedigree. The honest caveat is that these are internal tools for sales and marketing teams, not customer facing product engineering, so weigh that against the low bar to entry.
What the posting asks for: - 2 to 6 years of experience in cyber security, pre sales or consulting. Partner or channel experience is preferred but not required. - A strong understanding of cyber security fundamentals: web, cloud, SIEM, IDS and IPS, SOAR, email security, and threat intelligence or dark web work. - Familiarity with the cyber security ecosystem and how tools fit together in a SOC, across small, medium and large enterprises. - The ability to deliver demos and proofs of concept and explain solutions clearly. - Strong communication for both technical and business audiences, and good presentation skills. - A self driven, proactive approach. - Comfort working across sales, product, research and marketing. Counts as a bonus: - Certifications such as CompTIA Security+ or CISSP. The day to day: prospecting, onboarding and managing partner companies and helping them generate leads, training partners to understand and position the product, managing RFP and RFI responses and writing solution documents and sales proposals, running product demos, proofs of concept and customer presentations, working with sales teams and partners to close deals, organising workshops and webinars, sharing research and threat intelligence with partners, and representing partner feedback back inside CloudSEK. Experience: the posting states 2 to 6 years. That band is wide on purpose and the lower end is real. Location: Bengaluru, with travel as required to meet partners and customers. CloudSEK lists flexible working hours and food at the office. Company context worth knowing: founded 2015, headquartered in Singapore, Series A of 7 million dollars in 2021 led by MassMutual Ventures, and 19 million dollars raised in 2025 led by Tenacity Ventures and Commvault. It won the NASSCOM DSCI Security Product Company of the Year award in 2020. Who should apply: someone with a security background who is good in front of people and wants the commercial side without leaving the technology behind. This is a customer facing and partner facing job, so if you want to be heads down in a SOC, it is not for you.
What the posting asks for: - 3+ years of hands on experience in applied machine learning and data science, with a master's or PhD in computer science, machine learning, data science, statistics or a related field, or appropriate experience in place of the degree. - A strong background in machine learning, deep learning and NLP, with proven experience training and fine tuning large scale models such as LLMs, transformers and diffusion models. - Hands on expertise with parameter efficient fine tuning: LoRA, prefix tuning, adapters and quantization aware training. - Proficiency in PyTorch, TensorFlow and the Hugging Face ecosystem. - A basic understanding of MLOps: experiment tracking, model versioning, CI and CD for ML pipelines, and production deployment. - Experience with large datasets, feature engineering and data pipelines using Spark, Databricks or cloud native ML services such as AWS SageMaker, GCP Vertex AI or Azure ML. - Knowledge of GPU and TPU optimisation, mixed precision training and scaling ML workloads. - Excellent communication, including explaining complex ML concepts to non technical audiences. Marked mandatory in the posting: - Demonstrated success adapting foundation models to domain specific applications through fine tuning or transfer learning. - A strong ability to design, evaluate and improve models using robust validation strategies, bias and fairness checks, and performance optimisation. Counts as a bonus: - Distributed training frameworks such as DeepSpeed, PyTorch Lightning or Ray. - Proven ability to mentor junior applied scientists and ML engineers. Experience: the posting states 3+ years. Note the degree expectation is unusually explicit here, and the two mandatory skills are about fine tuning and evaluation rather than years served. Location: Bengaluru. CommerceIQ is headquartered in Mountain View with teams across the US, India, Canada and the UK. Who should apply: someone three or more years into applied ML who has actually fine tuned models rather than only called APIs. If your experience is dashboards and reporting, the mandatory requirements will screen you out, and MongoDB's data analyst role in today's list is a better fit.
What the posting asks for, at 3+ years of experience: - Knowledge of client server architectures and network design. - Solid knowledge of Cisco IOS and NxOS and other network operating systems. - Routing protocols including static routing, BGP and OSPF. - NAT, PAT and PBR. - Strong knowledge of L2 protocols. - WAN, LAN and data centre network architectures. - Network design, network operation or network automation. - Multicast configuration (PIM, IGMP). - Firewall and VPN technology including site to site VPN and GRE. - Knowledge of Unix or Linux. - Knowledge of data centre installation and cabling standards. Counts as a bonus: - Basic scripting, for example Python. - CCNA or higher. - Systems administration experience. The day to day: working with traders to add or change network connectivity to financial exchanges, troubleshooting and analysing network performance problems, helping design networks for new offices and data centres, finding low latency solutions in existing networks, supporting production, office and end user environments, performing market connectivity tests and circuit migrations, assisting with data centre migrations, liaising with third parties over communication lines and data centre infrastructure, and coordinating with remote hands technicians globally. Experience: the posting states the ideal candidate has 3+ years, and the skill list that follows is what those years should contain. Location: Gurugram, in office. Graviton describes cubicle free offices and a non hierarchical culture. Benefits listed in the posting: competitive compensation, an annual international team outing, fully covered commuting expenses, best in class health insurance, catered breakfast and lunch, four weeks of annual leave plus market holidays, gym and sports club memberships, and regular social events. Who should apply: a network engineer around three years in who wants low latency and exchange connectivity work rather than a corporate IT network. Trading firms pay well and expect precision, and the feedback loop when something is slow is immediate.
What the posting asks for: - 3+ years of software development experience in fast paced environments and modern stacks. - A strong technical foundation across any of frontend, backend, cloud, AI and ML, or DevOps. The posting names React, Angular, Node, Spring Boot, AWS, Jenkins and generative AI as examples. - A strategic but hands on product thinker, able to drive execution from concept to delivery. - Skill at working closely with engineers, speaking their language, and turning complex technical problems into clear product direction. - Comfort with tools such as GitHub, JIRA, Slack and analytics platforms. Counts as a bonus: - Contributions to open source. - Exposure to open source communities and other developer ecosystems. - Familiarity with AI driven workflows for scaling products. The day to day: building and managing a global network of experts who create coding challenges, owning the product roadmap for the coding challenge platform and content ecosystem, building tools that scale content delivery and support emerging technologies, partnering with customers to understand their workflows, using data and automation and AI to streamline content creation and review, and making sure everything shipped holds up on fairness, validity and developer experience. HackerRank says you will thrive here if you are a builder who likes creating scalable systems from scratch, are not slowed down by ambiguity, care about developer experience, and are energised by collaboration. Experience: the posting states 3+ years of software development experience. Location: hybrid in Bangalore, so factor in office days. Company context: HackerRank is used by over 2,500 companies including NVIDIA, Amazon and Microsoft, and positions itself around skills rather than pedigree. Who should apply: an engineer around three years in who is drawn to product and content work and wants ownership of a platform millions of developers touch. The honest caveat is that this is not a coding heavy role: the technical foundation is there so you can direct the product credibly, and the day to day is roadmap, tooling and expert network management.
What the posting asks for: - A BS or MS in computer science or a closely related technical field, or equivalent demonstrated experience. - 3+ years building ML training infrastructure or large scale distributed systems. The posting adds that exceptional early career candidates with a strong systems background will be considered, which is worth noting if you are under three years. - Hands on experience training large models with distributed training frameworks: Megatron LM, DeepSpeed, FSDP, NeMo or equivalent. The posting says you should have been on call for a real pretraining run. - Deep working knowledge of GPU architecture, the CUDA programming model, and profiling tools such as Nsight and the PyTorch profiler. - Strong PyTorch internals knowledge, comfortable reading and modifying low level training code rather than only using high level APIs. - Meaningful open source contributions in the training infrastructure ecosystem: Megatron, DeepSpeed, PyTorch, vLLM, Triton, NCCL or similar. Counts as a bonus: - Custom CUDA or Triton kernel development with measurable wins on real workloads. - Direct experience training models at 10B+ parameters or on 1000+ GPU clusters. - Cluster orchestration and job scheduling at scale (Slurm, Kubernetes). - Mixed precision (BF16, FP8), quantization aware training or similar numerical work in production runs. - First author papers or technical reports on training systems, scaling or model efficiency. The day to day: building and pushing the limits of the distributed training stack across large GPU clusters, designing parallelism strategies and reasoning about which combinations suit which architectures and scales, profiling and optimising end to end throughput including kernel performance, communication overlap, memory layout, checkpointing and data loading, writing and tuning custom GPU kernels, owning the reliability of long running jobs through fault tolerance and checkpoint integrity and deterministic restarts, and partnering with researchers and the data team. Experience: the posting states 3+ years, with an explicit exception for exceptional early career systems engineers. Location: Bengaluru. Who should apply: a systems engineer who wants frontier model training work without leaving India. Sarvam is direct that the bar is high and the cost of mistakes is measured in weeks. If you have real distributed training experience, very few Indian employers can offer this problem.
What the posting asks for: - 5+ years building infrastructure or platform software, with a track record of systems you designed and shipped. The posting is pointed about this: services and control planes others built on, not scripts and glue. - Strong software engineering in Go or Python, with the judgement to build maintainable systems and the depth to debug them in production. - Kubernetes at the controller and internals level. You should have written operators or controllers, understand the scheduler and API machinery, and know where the abstractions leak. - Working literacy in GPU specific platform constraints: MIG and GPU sharing, gang scheduling, topology and fabric aware placement, and why training and serving contend for the same hardware. - A product mindset toward internal users, measuring the platform by adoption and self service rather than tickets closed. - The range to own a capability end to end, from design through rollout to the documentation that makes it self serve. Counts as a bonus: - Having built a serving, inference or training platform: routing, autoscaling and rollout for model endpoints at scale. - GPU scheduling systems in multi tenant production (Kueue, Volcano, Slurm, Run:ai or custom). - Multi tenant isolation (MIG, MPS, time slicing) shipped as a self service capability. - Deep Kubernetes networking: CNI internals, custom network components, or RDMA and SR-IOV in pods. - On premise GPU platform work, including multi vendor or Indian NCP environments. - Open source contributions to Kubernetes, scheduling or GPU platform projects. The surface area, from the posting: the serving platform control plane with routing, canary and blue green rollouts and traffic splitting; the scaling and elasticity layer for both training and serving; scheduling and orchestration with gang scheduling, priority and preemption and quota enforcement; multi tenancy, RBAC and isolation; platform networking; observability and cost tooling; the storage and data path; developer experience through CLI, SDK and APIs; and provisioning through Terraform, Crossplane or operators. You would take one capability and build it end to end rather than own all of it at once. Experience: the posting states 5+ years. Location: Bengaluru. Who should apply: a platform engineer who has built control planes rather than maintained them, and who wants GPU scale problems. If your Kubernetes experience is writing manifests rather than controllers, the bar here is above you.
What the posting asks for: - A bachelor's degree in computer science, engineering or a related technical field. - 3+ years in conversational AI, solution engineering, system integration, or delivering AI and LLM based applications in customer environments. - Strong ability to lead customer facing discussions, from deep technical troubleshooting to weekly project demos, and to explain complex concepts to non technical audiences. - Strong hands on skills in prompt design, workflow building and API integration (SIP, Twilio, Amazon Connect and similar). - Familiarity with LLMs (GPT, Claude, Gemini), vector databases, and orchestration frameworks such as LangChain and LlamaIndex. - Working knowledge of retrieval augmented generation: concepts, implementation patterns and performance optimisation. - Programming experience in Python, JavaScript or similar for scripting and integrations. - A strong problem solving mindset, finding workarounds and adapting to each customer's ecosystem. Counts as a bonus: - Integration platforms such as n8n or Zapier, and proficiency in API integration and data flow management. - Familiarity with telephony or voice systems (SIP, CCaaS, PSTN). The day to day: owning AI agent implementation including prompt design, workflow configuration, integrations, telephony setup and evaluation frameworks; acting as the primary technical partner for customers through demos and feedback; configuring API integrations with authentication, data mapping and error handling; setting up SIP, CCaaS and PSTN routing and troubleshooting call quality; refining prompts and monitoring performance against automation and containment targets; and escalating platform gaps to product and engineering. Experience: the posting states 3+ years, and accepts several entry paths into that (conversational AI, solution engineering, system integration or software engineering with AI delivery). Location: Bengaluru. Benefits listed: medical insurance for self and family with free online doctor consultations, accident and group term life insurance, privilege and sick leave, parental leave, an annual learning and development allowance, and flexible tax benefits including meal cards. Who should apply: someone three or more years in who wants applied LLM work with a real deployment target and does not mind that the customer is in the room. If you want to train models, this is the wrong role and Sarvam's postings in today's list are the right ones.
What the posting asks for: - A bachelor's degree, with a technical major such as engineering preferred. An advanced degree is a plus. - 4+ years of experience in a similar role. - A solid technical background with a demonstrable understanding of AI and machine learning. - SaaS experience, which the posting marks as essential. - Experience with tools such as Zendesk, Confluence and JIRA. - Excellent client facing and internal communication skills. - Excellent written and verbal English. Counts as an advantage: - Python or other scripting experience. The day to day: front ending all customer reported issues, reviewing and troubleshooting them within the agreed SLA, managing customer expectations as the point of contact for service issues, proactively diagnosing and analysing problems on the platform, researching alternative solutions and workarounds, escalating internally and owning issues through to resolution, running regular tool upgrades and monitoring the platform, documenting issues and solutions into the knowledge base including SOPs and service notes and recorded videos, and becoming a subject matter expert on the platform. Experience: the posting states 4+ years in a similar role. Location: Bengaluru. What the posting offers beyond the work, in its own words: hands on exposure to real technical problems, a contribution to pre release testing and product quality, ownership, and compensation and benefits closer to a larger established company than the stage would suggest. Benefits listed include medical insurance for self and family with free online doctor consultations, accident and group term life cover, privilege and sick leave, parental leave, an annual learning and development allowance, and flexible tax benefits. Who should apply: a support engineer with four or more years on a SaaS product who wants to move towards AI products and eventually towards solutions or product roles. Readers asked for customer facing technical roles by name, and this is one of the more technical ones in that group.
What the posting asks for: - 3 to 5 years of hands on experience with IAM technologies and solutions. The header states the band as 3 to 6 years, and the posting adds that senior level candidates with broader security expertise will also be considered. - Demonstrated expertise in Microsoft Entra ID, including administration and configuration. - A solid understanding of AWS IAM: identity federation, cross account access and policy management. - Experience with at least one privileged access management solution: Delinea Secret Server, BeyondTrust, CyberArk or similar. - Strong understanding of authentication and authorisation protocols: OAuth, SAML, LDAP and Kerberos. - Knowledge of compliance frameworks: Zero Trust, NIST, SOC 2 and ISO 27001. - Excellent communication and documentation skills. Counts as a bonus: - SC-300 (Microsoft Certified Identity and Access Administrator Associate) or similar. - Experience designing and securing AI agent architectures and autonomous workflows, and hands on work with Copilot Studio agent security. - Knowledge of Model Context Protocol and agent to service authentication patterns. - RBAC model design across complex application ecosystems. - Automating provisioning and deprovisioning with Okta, ServiceNow or Microsoft Identity Manager. - Multi cloud experience (Azure, AWS, GCP), Zero Trust architecture, scripting in PowerShell, Python or Bash, and identity first incident response. The day to day: designing and maintaining identity governance in Entra ID including provisioning, authentication policies and conditional access; managing AWS IAM policies and roles across accounts on least privilege; running PAM to monitor and audit privileged activity; configuring MFA, SSO and federation across hybrid environments; running security audits and access reviews; integrating IAM with enterprise and SaaS applications; managing access for AI agents including scope limits, token management and service principal governance; designing RBAC models; automating provisioning and deprovisioning; and responding to identity compromise incidents. Experience: the posting gives 3 to 6 years in the header and 3 to 5 years in the required qualifications. We have published the wider band because the posting also invites more senior applicants. Location: Bengaluru. Who should apply: an IAM or cloud security engineer around three to six years in. The AI agent identity work is the differentiator: it is early enough that few candidates will have it, so a strong IAM background plus genuine curiosity about agent authentication is likely to be competitive.
What the posting asks for: - 4+ years, stated in the header, with total industry experience of around 4 to 7 years stated in the body. - A BTech, MTech or MS in computer science or a related field from a reputed university. - Programming experience in Python, Ruby, Perl or equivalent, which the posting marks as a must. - Good knowledge and experience of a configuration management tool such as Ansible. - Good knowledge and experience of provisioning tools such as Terraform. - Good knowledge and experience with AWS. - Experience setting up CI and CD pipelines. - Experience, in an individual capacity, managing multiple live SaaS applications with high volume, high load, low latency and 24x7 availability. - Experience setting up web servers such as Apache, application servers such as Tomcat or WebSphere, and both relational and NoSQL databases. - Good knowledge of UNIX and Linux administration tools. - Good knowledge of security best practices and tools such as firewalls and VPNs. - Good knowledge of networking concepts. - The ability to troubleshoot quickly. The day to day: writing scripts to build the infrastructure that keeps Netradyne's services available 24x7, setting up monitoring and alerting, troubleshooting issues reported across multiple environments, and triaging production issues with timely responses to customers. Experience: the posting states 4+ years in its header and around 4 to 7 years in the body, so we published the band. Location and work model, both stated explicitly in the posting: on site, five days a week in the office, at HM Tech Park in Whitefield, Bangalore, on a general shift. If you are looking for remote or hybrid, this one is neither, and today's list has nine remote roles instead. Company context: Netradyne is headquartered in San Diego with offices in San Francisco, Nashville, the UK and Bangalore, was founded in 2015, and reports growth exceeding four times year over year. Who should apply: a DevOps or SRE engineer with four to seven years who has personally carried production SaaS availability and lives near enough to Whitefield for a five day office week.
Mandatory skills from the posting: - Strong computer science fundamentals across data structures, algorithms and system design. - Deep hands on backend experience with Java and Spring Boot. - Strong grounding in distributed systems concepts: consistency, durability, retries, idempotency, backpressure, partitioning and resilience. - Practical experience with Kafka, Kinesis, Pulsar or similar. - Experience operating production systems, including on call, incidents and postmortems. - Excellent communication and technical leadership. Preferred: - Experience building high throughput ingestion or streaming systems. - Exposure to compliance heavy or audit driven domains such as transportation, fintech or healthcare. - Experience with edge or intermittently connected devices. - Hands on work with observability stacks. - Prior experience with ELD, HOS or telematics. The day to day, grouped as the posting groups it. Architecture and technical ownership: owning the architecture, design and evolution of platform services, driving system design for large cross service features from ingestion to downstream consumers, and defining clean service boundaries, APIs and data contracts. Platform and systems development: designing scalable high throughput ingestion pipelines for logs, telematics and event data, building streaming and batch workflows, translating regulatory requirements into system guardrails, and ensuring correctness, ordering, idempotency and fault tolerance. Reliability and observability: defining and upholding SLOs for latency, availability and data accuracy, championing logging, monitoring, tracing and alerting, and designing for backpressure, graceful degradation and recovery. Data modelling and storage: designing data models and partitioning strategies for hot and cold data and selecting between SQL, NoSQL, time series and object storage on scale, performance and cost. Plus cross team collaboration, design reviews and RFCs, and mentoring engineers. Experience: the posting states 6+ years in its header. Staff here is a senior individual contributor role with mentoring attached, not a management position. Location and work model: on site five days a week at HM Tech Park, Whitefield, Bangalore, general shift. Who should apply: a backend engineer with six or more years in Java who wants genuine scale and ownership of a domain rather than a feature team. The five day office requirement is the main thing to weigh.
What the posting asks for: - 3+ years of hands on analytics experience, with a focus on people or HR analytics preferred. - Advanced SQL, comfortable manipulating very large datasets. - Proficiency in Python or R with a strong focus on data wrangling and analysis. - Extensive experience with Tableau or another leading visualisation tool, which the posting marks as required. - Familiarity with data architecture fundamentals and data warehousing. - Proficiency with data modelling and data quality best practices. - Demonstrated ability to communicate and set priorities with stakeholders at all levels. - Highly collaborative and organised with strong attention to detail. - Comfort with ambiguity and the ability to work in a self guided way. Preferred but explicitly not required: - Experience analysing complex people data such as headcount, attrition, recruiting metrics and compensation. - Exposure to modern cloud data warehouses. The day to day: partnering with People teams across compensation, recruiting and talent development to understand their questions and turn analyses into recommendations, helping build the roadmap for people data investments, working with data engineering and HRIS to create and manage a curated central repository, designing automated dashboards so stakeholders can self serve, triaging analytical and reporting requests from across the People team, developing data governance and quality processes, and communicating findings to non technical audiences. Experience: the posting states 3+ years of hands on analytics experience. The domain preference is soft; the SQL, Python or R and Tableau requirements are the hard ones. Location: Gurugram, hybrid. MongoDB states it is looking to speak to candidates based in Gurugram for this model. Who should apply: an analyst three or more years in with strong SQL who wants a well defined stakeholder group and a chance to build the data foundation rather than inherit it. Be clear that this is people and HR data, not product or revenue analytics, which is a genuine specialisation and not everyone's interest. If the domain does not appeal, MongoDB's engineering roles in today's list are a different path.
What the posting asks for: - 5+ years of experience building distributed systems or foundational cloud services at scale, with an interest in working with Python, Go and Java. - A strong background building core components for high scale compute and data distributed systems. - Proven success designing, writing, testing, debugging and performance tuning, with a strong grip on computer science fundamentals, in large and long lived codebases. - A track record of identifying problems, implementing solutions and delivering complex projects in distributed systems or databases. - Good verbal and written technical communication and a desire to collaborate. - Eagerness to learn. Counts as a bonus: - Containerisation and orchestration platforms such as Kubernetes. - AI frameworks and tools. The day to day: working with research, product management, product engineering, product design and other teams to define the first version and future evolution of the service; designing, building and delivering well tested core pieces of the platform; contributing to architecture, code reviews, development practices and developer experience as the team and product grow; and mentoring other engineers while owning projects outright. Experience: the posting states 5+ years. Location: Gurugram, hybrid. MongoDB states it is looking to speak to candidates based in Gurugram for this working model. Company context: MongoDB has over 60,000 customers including 75 percent of the Fortune 100, and MongoDB Atlas runs across AWS, Google Cloud and Azure. Who should apply: a backend or distributed systems engineer with five or more years who wants greenfield work on a real product inside a large company, which is a rarer combination than it sounds. If you want the operational side of the same platform instead, MongoDB's Senior Site Reliability Engineer role is in today's list and sits on the same team.
What the posting asks for: - 6+ years of experience building and operating distributed systems, with proficiency in Python, Go or a similar language. - A strong background in software development and operating distributed systems. - Experience operating Kubernetes in production and debugging below the abstraction layer, including scheduling, cluster networking and node level issues. - Expertise in cloud infrastructure platforms: AWS, Google Cloud or Azure. - A strong understanding of Linux internals and networking concepts such as TCP/IP, DNS, TLS and routing. - A customer focused mindset and strong technical communication. - A strong bias for efficient processes, operational simplicity and automation over manual work. Counts as a bonus: - Kubernetes networking such as Istio or Cilium, service mesh or edge load balancing in production. - Secure multi tenant runtime environments at scale. - Multi cloud infrastructure management. - Virtualisation or workload isolation technologies. The day to day: operating and improving the multi tenant Kubernetes infrastructure that runs customer workloads, building for reliability so services and infrastructure are available, resilient, fault tolerant and self healing, identifying and configuring the key metrics that detect incidents and quantify service health and performance, taking part in a 24/7 on call rotation to resolve platform infrastructure issues, and mentoring early career SREs while shaping the team's operational practices. Experience: the posting states 6+ years. On call: a 24/7 rotation is stated explicitly in the posting. Factor that in rather than discovering it at offer stage. Location: Gurugram, hybrid. MongoDB states it wants candidates based in Gurugram for this model. Who should apply: an SRE with six or more years who wants Kubernetes at multi tenant scale and is comfortable being early on a platform team, which means writing the operational practices rather than following them. If you would rather build the platform than run it, the Senior Software Engineer role on the same team is in today's list.
What the posting asks for: - A bachelor's degree in computer science, information technology, business or a related technical discipline. - 4 to 8 years of progressive, deep technical experience in IT infrastructure, system engineering and workplace operations. - Subject matter expertise in Jamf Pro, Apple Business Manager and corporate device enrolment profiles. Active Jamf certifications (200, 300 or higher) are highly preferred. - Master level administrative knowledge of corporate Google Workspace and Microsoft 365. - Deep technical understanding of IDaaS, single sign on integrations, SAML and OIDC protocols, and lifecycle provisioning through Okta or Azure AD. - Exceptional troubleshooting on modern macOS and Windows, with the ability to write Bash and PowerShell scripts to automate repetitive work. - A proactive, consultative approach, with the presence to mentor junior peers and explain complex systems to non technical stakeholders. The day to day: acting as the subject matter expert for internal infrastructure and handling advanced L3 escalations and complex architectural challenges, administering and tuning Google Workspace and Microsoft 365 at global configuration level, owning and scaling endpoint device management as the technical authority for Jamf Pro and Intune, designing and deploying automated identity provisioning and access governance integrations with Okta and Entra ID, leading user lifecycle automation for onboarding and offboarding and role changes, partnering with information security on endpoint compliance and threat isolation and conditional access and data classification, writing technical runbooks and SOPs to upskill junior helpdesk engineers, and driving automation with scripting and cloud platforms. Experience: the posting states 4 to 8 years. Location: Pune, on Mindtickle's growing infrastructure team. Company context: Mindtickle is recognised as a market leader by industry analysts, won an AI Breakthrough award for AI based sales solution of the year, and holds a Gold Stevie award for sales and customer service. Who should apply: an IT infrastructure engineer four to eight years in who has outgrown a helpdesk queue and wants ownership of endpoint and identity platforms globally. This is a good fit if you enjoy automation and being the last escalation, and a poor fit if you are aiming at product engineering, since the customers here are Mindtickle's own employees.
What the posting asks for: - 5+ years of experience with PHP, Node.js and relational databases such as MySQL or Postgres, plus Kafka, RabbitMQ and React. - Profound experience in backend development. - Experience with object oriented programming. - Experience designing APIs. - Experience with event based distributed applications. - A focus on clean and readable code. - Source code management with Git. - The ability to work in a team and a willingness to take part in an open feedback culture. The day to day: working with other developers to align on project goals, architecture and delivery timelines; implementing and maintaining scalable software in PHP while balancing technical excellence against pragmatic delivery; using GitOps, Kubernetes and related tools to streamline deployment and infrastructure management; and taking part in architecture discussions, bringing new ideas and constructively challenging others. You would report to a Software Engineering Manager. Experience: the posting states 5+ years, and lists the specific technologies inside that same requirement rather than separately, so the years are expected to include PHP and Node.js. Location: Bangalore. A note on the title: the posting is listed as Software Engineer but the description opens with "As a PHP Developer", so the role is squarely backend PHP work. If PHP is not a language you want on your next CV line, that is worth knowing before you apply rather than after. Company context: ChargePoint has focused solely on electric mobility since 2007 and trades on the NYSE as CHPT. The posting frames electric vehicles as heading toward more than half of new vehicle sales by 2040. Who should apply: a backend engineer with five or more years in PHP and Node who wants scale and a sector with a long runway. Charging networks are real infrastructure work with genuine reliability requirements, which makes this more interesting than a generic PHP posting.
What the posting asks for: - 10+ years of software engineering experience with significant exposure to distributed systems and cloud native architectures. - Strong expertise in observability: monitoring, logging, distributed tracing, telemetry pipelines and incident management. - Experience operating large scale production systems with a focus on reliability, scalability and performance. - Deep understanding of system debugging, root cause analysis, performance optimisation and production operations. - Strong programming experience in one or more of Go, Java, Python, Node.js or similar. - Experience with observability technologies such as OpenTelemetry, Prometheus, Grafana, Elasticsearch, Datadog, New Relic, Splunk or Honeycomb. - The ability to influence technical direction across teams without direct authority. - Strong communication and a data driven approach. Counts as a bonus: - Building internal developer platforms or observability platforms at scale. - Exposure to AIOps, intelligent alerting, anomaly detection or AI powered operational tooling. - Driving reliability initiatives across multiple engineering organisations. - A background in SRE, platform engineering, infrastructure engineering or developer productivity. The day to day: driving the technical vision and architecture for Postman's observability platform, designing scalable solutions for metrics, logging, tracing, alerting and operational analytics, investigating complex production issues and driving long term corrective action, partnering with engineering teams on reliability and operational maturity, establishing observability standards and instrumentation frameworks, building tooling and automation for faster incident detection and resolution, using telemetry to find performance bottlenecks and capacity risks, and mentoring senior engineers. Experience: the posting states 10+ years. This is the clearest title mismatch in today's list: the role is advertised as Senior Engineer, but the opportunity section says "We are looking for a Staff Engineer" and the requirement is 10+ years. Do not rule yourself in or out on the title. Location and office days, stated explicitly: Postman values in person collaboration. Bangalore based employees currently work in the office three days a week and will move to five days a week by the end of the year. That is a material change and worth weighing now rather than later. Who should apply: an experienced platform, SRE or infrastructure engineer who likes diagnosis and wants company wide scope. If you are a senior engineer at six or seven years, the title will tempt you but the stated bar will not stretch that far.
Added July 23, 2026
What the posting asks for: - About 1 year of experience handling cases in compliance, fraud, risk or trust and safety (the role states 1 to 3 years and welcomes people early in their careers). - Fluent written and spoken English, since almost all of the work is written customer contact. - A habit of writing clear internal and external documentation. - Comfort with critical thinking to spot and stop fraudulent activity. The day to day: you respond to customers over email, chat and calls, guide them through compliance and account verification, evaluate alternatives when something is blocked, and resolve account suspensions. You file clean internal reports and add to the knowledge base as you go. Location and hours: fully remote within India. This is a 24/7 team, so expect a rotating shift schedule that can include one or both weekend days. Read the shift terms before you apply. Honest read: one of the few genuinely entry friendly, fully remote roles on this list. It is customer facing support rather than software development, so pick it if you like the investigative, people facing side of a technical product.
What the posting asks for: - 3+ years of hands on Salesforce development with Apex, Lightning Web Components (LWC) and SOQL. - Experience with Apex controllers, Apex web services, Apex callouts and integration design. - The judgement to understand the underlying business problem, weigh solution alternatives, and balance speed against quality. - Comfort managing large volumes of data and building reportable, intuitive systems for non technical end users. The day to day: you evolve a Salesforce data model that stays scalable and reportable, build custom functionality with Apex and LWC, take part in technical analysis and integration design with architects, review incoming code, and refactor the existing codebase for maintainability. Location: fully remote within India. Honest read: this is a software development role, but it lives on the sales systems side of the house. If you are a Salesforce engineer who wants to work closer to the business and own more than tickets, it fits. If you want product engineering away from CRM, it will not.
What the posting asks for: - Overall 3+ years of experience, with a deep understanding of email infrastructure and deliverability. - Strong technical troubleshooting plus the diplomacy to handle customers whose issues carry costly, far reaching consequences. - Ability to read APIs and SDKs well enough to act as a subject matter expert. - Comfort filing reproducible bug reports (JIRA) and collaborating with product and engineering over Slack. The day to day: you resolve customer issues over the support channel, feed customer signal back to product and engineering, work with developers and architects on complex problems, and contribute to internal and external documentation. Location and hours: remote within India, supporting EMEA. Current shift is 12pm to 9pm or 1pm to 10pm IST, on a five day roster (Mon to Fri, Tue to Sat, or Sun to Thu) that can include weekend days. Confirm the shift before applying. Honest read: a remote, mid level support engineering role for someone who already knows email or messaging infrastructure. The shift timing is the real trade off, so weigh it honestly.
What the posting asks for: - 8+ years writing production grade code, with real experience building and operating high scale distributed systems (several thousand events per second and processing engines handling 1M+ events per second). - A Bachelor's or Master's in Computer Science, Engineering or a related field. - Depth in designing for high availability, throughput and eventual consistency, plus reliability and security of the platform. - The ability to act as a team tech lead and mentor other engineers on architecture. The day to day: you design and ship high scale routing for the Segment data pipelines, build and optimise globally available distributed systems, partner with product and other Segment teams, and support platform reliability and security. Location: fully remote within India. Honest read: a genuine Staff level distributed systems role. Twilio notes it welcomes non traditional paths, but the 8+ year bar and the 1M events per second scale are real. Best for engineers who have operated data platforms at scale and want a remote seat with technical leadership.
GitLab does not state a years requirement anywhere in this posting, so we have left the experience figure blank rather than invent one. Judge fit on the substance below. What the posting asks for: - Strong backend engineering in Go, applied to high throughput, multi component systems. - Experience with core system design: ingestion, transport, replication, query serving and query oriented storage. - Familiarity with the surrounding stack: ClickHouse or similar column stores, NATS or comparable messaging, gRPC, and deployment across multiple environments. - Comfort owning reliability, operability and production readiness end to end. The day to day: you design and evolve Go backend services for the Data Insights Platform and Siphon, own significant parts of the architecture including the gRPC integration with GitLab Rails, and drive safe rollout across SaaS, Dedicated and Self Managed environments. Location and ways of working: GitLab is all remote and asynchronous. The posting is tagged Bangalore, India, which in GitLab terms means remote within India. Some GitLab roles carry location based eligibility, so confirm yours. Honest read: a strong remote backend role for a Go engineer who likes data infrastructure. No stated years, so do not rule yourself out on seniority alone.
GitLab does not state a years requirement in this posting, so the experience figure is left blank rather than guessed. This is a Staff level role, so expect the bar to be high. What the posting asks for: - Strong distributed systems instincts: durability, tenant isolation and horizontal scalability, and the judgement to tell a design that is durable from one that only looks durable under light load. - Go backend depth and the ability to decompose complex architecture into shippable work for a team. - Experience owning reliability end to end and migrating production workloads off legacy systems without disruption. The day to day: you lead technical execution on the consolidated messaging and event platform, solve high complexity problems, set and hold the technical bar, and own the migration of existing production traffic off Sidekiq and the legacy event bus. Location and ways of working: all remote and asynchronous. Tagged Bangalore, India, meaning remote within India in GitLab's model. Some roles carry location based eligibility, so confirm yours. Honest read: a rare remote, Staff level distributed systems seat with real architectural ownership. Narrow pool, since durable multi tenant messaging is a specific skill, which cuts both ways.
GitLab does not publish a years figure for this role, so we have left it blank. It is pitched at Senior level, hands on. What the posting asks for: - Strong engineering skills combined with systems thinking and genuine business understanding. - Practical fluency with LLM and agent based systems, and the judgement to know when AI is not the right tool. - The ability to own initiatives end to end, from stakeholder discovery and design through deployment and iteration. - Comfort delivering working prototypes fast and measuring real outcomes. The day to day: you diagnose business problems before building, map workflows and constraints, and ship AI powered solutions into Sales, Marketing and Customer Support systems. You take ownership from discovery to production and iterate on what the data shows. Location and ways of working: remote within India, asynchronous, reporting to the Director, Enterprise AI. Some GitLab roles carry location based eligibility, so confirm yours. Honest read: an applied, internal facing AI engineering role for someone who leads with the problem, not the model. If you want frontier model research this is not it. If you want to ship AI that changes how a company works, it is a strong remote option.
What the posting asks for: - 3+ years building large scale data systems (petabyte scale processing, distributed data pipelines or comparable). Exceptional early career candidates with a strong systems background will also be considered. - A BS or MS in Computer Science or a closely related field, or equivalent demonstrated experience. - Hands on experience with data curation and filtering for LLM training, and the ability to defend the choices in a corpus you helped build. - Depth in distributed data frameworks (Spark, Ray, Beam, Dask or equivalent) and the storage underneath, plus strong Python and comfort with tokenization, sharding, packing and IO tradeoffs. Nice to have: experience with large open pretraining corpora, model based quality classifiers, contamination detection, or data attribution research. The day to day: you build ingestion, parsing, filtering, dedup, tokenization and packing pipelines at petabyte scale, improve quality filtering, own mixture and curriculum design with the research team, and build tooling so researchers can slice and debug the data. Location: Bengaluru. Honest read: a serious data engineering role at a pretraining lab. The 3+ years is a soft floor, so strong systems focused early career engineers should still consider it.
What the posting asks for: - 3 to 5 years in frontend engineering, shipping production web applications. - Strong React and TypeScript (hooks, context, custom abstractions, performance optimisation), described as non negotiable. - Hands on Next.js with the App Router, server components, API routes and middleware, also non negotiable. - Experience with state management at scale (React Query, Redux, Zustand or similar). The day to day: you build Studio's core media workflows (video and voice dubbing, voice cloning), own a visual node based pipeline editor, implement real time job progress tracking, build in browser recording and media playback, work in a Next.js monorepo, extend a shared design system, and instrument features with analytics and error monitoring. Location: Bengaluru, high ownership role on a small team. Honest read: an unusually substantial frontend role, closer to product engineering than UI work, at an Indian AI company solving hard media problems. If you want deep React and Next.js work with real product impact, it fits well.
What the posting asks for: - 5 to 10 years building production backend systems, with deep Python and FastAPI (or Golang). - A track record of full stack ownership: designing systems end to end, making the tradeoffs, and operating them in production. - Hands on workflow orchestration at scale, ideally Temporal. - Strong PostgreSQL and Redis fundamentals (schema design, query performance, caching strategy), and experience with high scale, multi tenant, low latency distributed systems. Nice to have: building products on top of LLMs or ML systems, a telephony, VoIP or SIP background, and time at an early or growth stage startup. The day to day: you own the backend for agent, campaign and user management from data model to deployment, run workflow orchestration with Temporal, own performance and reliability at sub second SLOs, build observability and integration testing, and set a design first, documentation first culture (RFCs before code). Location: Bengaluru. Pure individual contributor Staff role, no people management. Honest read: a strong senior backend seat for someone who wants system ownership without moving into management.
What the posting asks for: - 4+ years preferred, but Sarvam hires across levels: strong AI fundamentals, range across the stack, high agency and a clear track record of shipping matter more than years. - A technical degree in Computer Science, Electrical Engineering or equivalent. - Deep, practical understanding of how LLMs and agents work in production: context engineering, memory, RAG, tool use, structured outputs and real failure modes. - Experience with agentic frameworks (LangGraph, LlamaIndex, Google ADK or equivalent) and both open and closed source models. Nice to have: deploying AI systems in regulated environments (BFSI, public sector) or with on premise and VPC deployments. The day to day: you embed with clients, scope and design end to end AI systems, build integration scripts and platform configuration, deploy into the customer environment, set up evaluations that measure whether the system works, and bring field learnings back to product and research. Location: Bengaluru, client facing engineering role. Honest read: an engineering role, not a support one, but one where half the job is with customers. It suits a high agency generalist. Because Sarvam hires across levels, do not rule yourself out on years alone.
What the posting asks for: - At least 5 years as a Machine Learning Engineer, with proven experience taking ML systems to production. - Strength across the full lifecycle: data ingestion, model development, deployment and monitoring. - Solid MLOps practice: logging, monitoring and CI/CD pipelines for distributed ML systems. - Comfort researching and rapidly prototyping emerging AI and ML frameworks, then driving full scale implementation. The day to day: you design and deploy production grade Gen AI and ML systems, implement and maintain MLOps, evaluate and prototype new frameworks, mentor junior engineers on system design, and translate business needs into technical solutions with cross functional teams. Location and ways of working: hybrid, based in Bangalore, reporting to the Sr. Manager, Engineering Strategy, Planning and Analytics. Honest read: a hands on Staff ML engineering role inside a security business, strong for someone who likes owning production ML and MLOps end to end. It is hybrid Bangalore, not remote, so factor in office days. Mentoring is expected but it is an individual contributor seat.
What the posting asks for: - 4 to 10 years of deep technical support, cloud support or escalation engineering experience. - Strong hands on troubleshooting across cloud security services, configuration, policy engines and APIs. - The ability to do detailed log, telemetry and packet level analysis, reproduce complex defects, and write engineering ready bug reports. - Willingness to own an on call rotation for the highest severity issues. Useful here: exposure to the secure use of AI models, governance of AI agents, data protection and inference security. The day to day: you resolve the highest severity escalations end to end, troubleshoot complex issues across the platform, investigate AI security scenarios, perform root cause analysis, and drive cross functional collaboration with engineering to validate fixes. Location and ways of working: hybrid, based in Bangalore (Mohali also listed), reporting to the Escalation Manager within Customer Success. Honest read: a senior, customer facing technical role that is squarely in scope for the readers who asked for escalation and customer success engineering. It manages accounts and incidents, not people. Hybrid Bangalore, with on call, so weigh both.
What the posting asks for: - 5+ years as a Software Development Engineer, with real strength in automation. - Hands on Python and the ability to design and maintain scalable automation frameworks and internal tooling. - Experience with networking concepts, since the products are network security systems. - Depth in scalability, stress and performance testing. The day to day: you design, implement and run comprehensive automated test cases for complex features, build and maintain automation frameworks that streamline the testing lifecycle, and lead performance and stress testing to find bottlenecks across web filtering, firewall, policy enforcement and CASB products. Location and ways of working: hybrid, based in Bangalore, reporting to the Sr Manager of Engineering in Cyber Security and Data Protection. Honest read: read the title carefully. This is a senior automation and quality engineering role inside a security business, not a feature development seat. If you are a strong SDET or automation engineer with Python and networking, it fits. If you want to write product features, it will not. Hybrid Bangalore, so factor in office days.
What the posting asks for: - 0 to 3 years in a technical support or customer facing technical role. Strong freshers with demonstrated technical aptitude are explicitly welcome. - A basic understanding of REST APIs: HTTP methods, status codes, and how to read a request and response. - The ability to read logs, browser developer tools and error messages to understand what happened before escalating. - Familiarity with SQL: enough to write or understand a basic query. - Comfort using AI tools to speed up investigation. The day to day: you own first response within SLA, resolve standard issues independently, triage and escalate complex tickets with full context, keep the queue healthy during your shift, maintain ticket hygiene, and contribute to the knowledge base. Location and hours: hybrid in Bangalore, on a rotational shift covering mornings, evenings and weekends for 24x7 global coverage. Honest read: a real entry level, customer facing technical role with a stated path into the next level. It is support, not development, and it involves shift work, but for someone early in their career who wants a technical foot in the door it is one of the honest 0 to 1 options here.
What the posting asks for: - 2 to 7 years in technical support or product support for a B2B SaaS platform. - Strong debugging instincts across web applications, REST APIs and third party integrations, tracing failures to root cause rather than the surface error. - Solid SQL: you write your own queries to investigate data issues and validate behaviour. - Working knowledge of SSO, SAML and OAuth flows. The day to day: you own complex escalations end to end, debug platform, API and integration failures, collaborate with engineering on confirmed bugs, lead incident management and customer facing RCAs for high severity issues, manage many open tickets without losing SLA, and turn recurring patterns into runbooks. Location and hours: hybrid in Bangalore, with a rotational on call that can include occasional late night or weekend coverage. Honest read: a mid level, customer facing technical role with real debugging depth, one of the customer success and support seats readers asked for. It is support engineering, not product development, and it carries on call, so weigh both against what you want.
What the posting asks for: - A degree in a highly analytical field such as Engineering, Mathematics or Computer Science, from a strong university. - 3+ years of experience with Python and Shell or Bash scripting. - Working knowledge of Linux and command line tools. - Strong problem solving and analytical skills, and clear communication. - Some mentorship experience guiding junior developers. The day to day: you build software tools that help quants run analysis and simulations, build scalable post trade systems that analyse statistics across all production strategies, implement tools for centrally analysing market data across exchanges, and write comprehensive C++ and Python scripts for risk attribution and performance breakdowns. Location: Gandhinagar, Gujarat. Graviton lists strong perks (covered commuting, catered meals, health insurance, international team outing). Honest read: a tools engineering role inside a quant trading firm, C++ and Python heavy and data intensive. You do not need to be a quant, but you should enjoy building infrastructure that quants use. Note the location is Gandhinagar, not one of the metros, which matters if relocation is a factor.
What the posting asks for: - 4+ years with Terraform for infrastructure as code. - 4+ years in configuration management and systems engineering supporting large scale Agile environments. - 4+ years of Linux or Windows administration, and 4+ years with Git and solid branching and merging strategy. - 2+ years hands on with AWS infrastructure and platform services, cloud automation tools (Ansible or Chef), and container orchestration (Kubernetes on EKS, ECS, Docker). Nice to have: experience across AWS, Azure and GCP. The day to day: you automate infrastructure with Terraform and CloudFormation, own the build and release cycle end to end, deploy releases and handle operations, improve the operations tooling (Jenkins, monitoring with Consul, metrics with Graphite and Grafana), migrate and retire legacy infrastructure, and set operational best practices. You work client facing, embedded with customer teams across the US and India. Location: Mumbai. Honest read: a senior, client facing DevOps role at a delivery focused firm that is honest about how agents change the work. The real floor is 4+ years across several areas, not the incidental 2+ some parsers pick up. Good for someone who wants ownership of migrations and carries delivery dates personally.
What the posting asks for: - 5+ years as an Oracle and PostgreSQL DBA and database developer. - Strong hands on experience with Oracle Database and PostgreSQL or Aurora PostgreSQL, and real Oracle to PostgreSQL migration work. - Advanced SQL and query performance tuning, plus PostgreSQL internals (indexing, statistics, execution plans). - Experience with AWS SCT and AWS DMS, and with a schema migration tool such as Flyway or Liquibase. Nice to have: AWS services (RDS, Aurora, CloudWatch, IAM), automation tools (Ansible, Chef, Puppet), IaC (Terraform, CloudFormation), and AWS Database Specialty or Solutions Architect certification. The day to day: you convert Oracle SQL and PL/SQL to PostgreSQL, remediate AWS SCT findings, manage the Flyway migration codebase, support and monitor AWS DMS through full load and CDC, tune PostgreSQL queries, and validate and reconcile data between Oracle and PostgreSQL. Location: Mumbai. Honest read: a specialist database migration role, not a general backend seat. If you have lived through heterogeneous Oracle to PostgreSQL migrations, this is squarely for you. If your database work is incidental, it will be a stretch.
What the posting asks for: - 8 to 12 years of professional experience in database architecture and migration delivery. - Hands on expertise with AWS DMS and AWS SCT for enterprise scale migrations. - Deep proficiency across Oracle, SQL Server, PostgreSQL and Aurora PostgreSQL, and a track record of heterogeneous migrations across on premises and cloud. - Skill authoring and executing migration runbooks, validation plans, cutover procedures and rollback strategies. The day to day: you lead migrations end to end (assessment, planning, schema conversion, execution, post migration validation), design and manage the DMS and SCT environments, convert Oracle PL/SQL and SQL Server T-SQL to PostgreSQL PL/pgSQL, author the cutover runbooks, drive migration testing and production readiness reviews, and provide technical leadership and governance to migration teams. Location: Mumbai. This is customer facing, enterprise migration delivery. Honest read: a senior, lead level database migration role. It carries technical leadership of teams but the core is deep hands on migration engineering, not people management. Best for a database migration specialist who wants ownership of whole enterprise programmes.
What the posting asks for: - 4 to 7 years in a relevant field such as ETL and ELT, data transfer or data warehousing. - A solid grasp of data integration: connecting diverse sources to a warehouse. - Helpful: experience with API integration and JSON and XML data formats. - The consultative instinct to make strategic technical recommendations and be the single point of contact for a customer. The day to day: you manage a book of customers and own their retention, engage as a technical advisor through the post sales lifecycle, run onboarding for new customers, build and develop data pipelines, build out of the box solutions when you hit product limits, drive engagement and adoption, and lead quarterly business reviews. Location: Bengaluru, reporting to the Head of Customer Success. Honest read: a customer success role with real technical substance, not an account management seat. It carries a book of business and retention responsibility, so there is a relationship and outcomes side alongside the pipeline building. Strong fit if you have data or ETL experience and want to be customer facing.
What the posting asks for: - 5+ years of hands on experience in applied machine learning and data science. - A degree in Computer Science, Machine Learning, Data Science, Statistics or a related field. - A strong background in machine learning, deep learning and NLP, with proven experience training and fine tuning large scale models (LLMs, transformers, diffusion models). - Hands on expertise with parameter efficient fine tuning (LoRA, prefix tuning, adapters, quantization aware training). - Proficiency in PyTorch, TensorFlow and the Hugging Face ecosystem, plus a basic understanding of MLOps (experiment tracking, model monitoring). Nice to have: distributed training frameworks such as DeepSpeed, PyTorch Lightning or Ray. The day to day: you build and fine tune large models for production, apply efficient fine tuning and quantization techniques, and ship AI capabilities into the workflows of large brand customers. Location: Bengaluru. Honest read: a hands on applied ML role, senior individual contributor, at a company shipping AI into enterprise commerce. Lead is a seniority marker here, not a management title. Strong for someone who wants modern model training work that reaches production.
What the posting asks for: - 5+ years in business intelligence, analytics engineering, data engineering or a similar role. - Strong SQL for data transformation, and comfort in at least one functional or object oriented language such as Python or Scala. - Expertise building reporting and data visualisation with tools like Looker, Tableau or Sigma. - Familiarity with database fundamentals (S3, Trino, Hive, Spark) and SQL performance tuning, plus experience writing data quality checks (Pydeequ, Great Expectations). The day to day: you translate business needs into data requirements, build and maintain canonical datasets and high volume ETL and ELT pipelines, lead the development of self serve data products, design metrics and dashboards, and champion high data integrity, reusability and standardisation across domains. Location: Hyderabad. Honest read: a strong, technical data role that leans analytics engineering rather than pure platform work. If you enjoy modelling data and building the datasets and tools the whole company relies on, it is a good fit. The 5+ years and SQL depth are real.
What the posting asks for: - 5+ years of software engineering experience building production systems. - Strength in Java, Python and TypeScript for building integrations and microservices with a focus on quality and reliability. - Interest and some ability in applying GenAI: building AI assisted automations and MCP integrations, and evaluating new models. - The temperament to partner with Finance and cross functional teams and translate their needs into integrations and reporting. The day to day: you build and maintain Finance integrations and microservices, contribute to the in house integration and no code platforms, design AI assisted automations and MCP integrations, migrate integrations off Oracle Cloud, and uphold quality through code reviews, testing and monitoring. Location: Bangalore. Honest read: a backend and integrations engineering role inside Airbnb's internal tech org, with a genuine modern AI tooling angle. The domain is enterprise and finance systems rather than the consumer product, so pick it if reliable integration work with a GenAI twist appeals. The 5+ year bar is real.
What the posting asks for: - 5 to 7 years of software engineering with a strong focus on frontend development. - Strong hands on React and TypeScript in production environments. - Experience designing and building scalable, high performance web applications, and with frontend testing frameworks such as Vitest, Jest and React Testing Library. - Working knowledge of backend systems, REST APIs and distributed systems, and comfort with backend for frontend and API layer changes. Nice to have: experience with design systems or shared component libraries. The day to day: you lead development of complex frontend features, translate ambiguous requirements into scalable solutions, own end to end delivery from design to production, drive improvements in UI architecture and performance, lead code reviews, set frontend standards, and mentor junior engineers. Location: Noida. Honest read: a senior frontend engineering role with genuine architectural ownership and a mentoring element, at a security intelligence company. It is frontend first but expects some backend fluency. Good for an experienced React engineer who wants to lead technical direction without moving into management.
What the posting asks for: - 7+ years in Linux and Unix administration, with extensive hands on experience. - Strong computer networking, including IP, iptables and IPsec. - Broad familiarity with open source technologies and tools, with an emphasis on cloud services. - Working experience with MySQL (MariaDB or Percona a plus), and coding and scripting skills, preferably Perl, Python or Golang. - Willingness to take part in the on call rotation. The day to day: you keep PhonePe's services always up and always available, apply IT operations best practices, work across a wide range of open source and cloud tooling, manage Linux networking and databases, automate with configuration management, and participate actively in on call. Location: Bangalore. Honest read: a senior, hands on SRE role at very high scale, weighted toward operating system, networking and database operations rather than software development. The 7+ year bar and the on call are real. Strong for a systems focused SRE who wants a high scale fintech environment.
What the posting asks for: - An active Elastic Certified Engineer certification (mandatory). - A minimum of 7 years as a Consulting Architect or in a senior IT role. An alternative path is accepted: at least 2 years as a Security Analyst working with SIEM tools such as Splunk, ArcSight or IBM QRadar. - Deep hands on Elastic Stack expertise: data modelling, query development and optimisation, cluster tuning and scaling. - Senior level consulting skills: workshop facilitation, requirements gathering, stakeholder communication and customer advocacy. The day to day: you deliver end to end Elastic projects for enterprise customers, run strategy, roadmap, design and sizing workshops, build proof of concepts, tune and scale clusters for fast search and analytics, and feed field learnings back to product, engaging with the sales team to scope opportunities and assess technical risk. Location and travel: based in India, with remote work plus required on site client engagement across time zones. Honest read: a senior customer facing consulting and solutions architecture role, not an internal product seat. The Elastic Certified Engineer requirement is a hard gate. Best for an experienced Elastic or security analytics specialist who likes client delivery and travel.
What the posting asks for: - 6+ years of experience in technical support, field engineering or a similar customer facing technical role. - A degree in Computer Science, Engineering (Mechanical or Electrical) or another technical field. - Strong troubleshooting and root cause analysis across software and connected hardware systems. - The ability to act as the primary technical authority and the bridge between customers, field teams and R&D. Helpful here: exposure to compliance or regulatory systems (DoT and FMCSA, ELD, Hours of Service), telematics or IoT. The day to day: you own the most challenging escalations on the ELD compliance product, ensure accurate recording of Hours of Service and Records of Duty Status data, reproduce and root cause complex issues, and work across customers, field teams and R&D to protect data integrity. Location: Bengaluru, within the Global Technical Support organisation. Honest read: a senior, customer facing technical support role with a compliance and IoT flavour, not a software development seat. The subject matter (US transport compliance) is specialised, so it suits someone who enjoys owning a complex product domain end to end. The 6+ year bar is real.
Cloudflare does not state a specific years figure in this posting, so we have left the experience number blank rather than guess. It is pitched as a senior, customer facing technical role. What the posting asks for: - A trusted technical advisor profile: someone who can own the technical relationship from discovery through adoption and expansion. - Strength across Cloudflare's portfolio: security, networking and developer platforms. - The ability to lead technical discovery, design bespoke architectures, and deliver compelling demos and proofs of concept. - Comfort operating as a quota carrying technologist within a go to market org, using AI augmented workflows to cut administrative work. The day to day: you partner with Account Executives on technical discovery, build architectures and proofs of concept, act as the continuous technical advisor through onboarding, renewal and expansion, and drive measurable business outcomes across the customer journey. Location and ways of working: fully remote within India, based in Mumbai, reporting to the Regional Customer Engineering Leader within the GTM organisation. Honest read: a pre sales and solutions engineering role, technically deep but quota carrying, so it has a commercial edge that a pure engineering seat does not. It is fully remote within India, which is its standout feature. Strong for a solutions or sales engineer who wants a remote, customer facing technical career.
Added July 22, 2026
What the posting asks for: a degree in a highly analytical field such as Engineering, Mathematics or Computer Science, and up to 2 years of experience with Python and shell or Bash scripting. You need working Linux and command line skills, hands on experience with SQL and NoSQL databases, strong problem solving and analytical ability, clear communication, and the temperament to stay calm and methodical while production is broken. Nice to have, not required: familiarity with monitoring and alerting stacks such as Prometheus, Grafana or ELK, exposure to Kafka and Redis, experience with CI/CD pipelines and deployment automation, and any prior time in a support, SRE or production engineering role. The real day to day: monitoring production services and trading systems, responding fast to alerts, incidents and outages, triaging across trading support services, databases and infrastructure, escalating to the right owners, and driving fixes to completion. You will also build automation to cut repeated manual work, improve observability by extending monitoring, logging and alerting, and maintain operational runbooks and SLO and SLA metrics. Location and setup: Gurugram, Haryana, on site. Graviton describes an open plan office with no cubicles, catered breakfast and lunch, a stocked kitchen, 6 weeks of paid vacation and an international team outing. Honest fit guidance: read the phrase "up to 2 years" as an upper bound, not a floor, which makes this reachable straight out of college if your Python, Linux and database fundamentals are solid. It suits someone who likes operational work and debugging live systems more than greenfield feature building. Trading support means production pressure and incident response are the job, not an occasional interruption. The posting does not publish an interview process.
What the posting asks for: a Bachelor's degree in computer science or a related field, proficiency in Linux and C or C++, and strong problem solving with the ability to work independently. Netradyne states the experience range as 1 to 3 years. Nice to have, not required: familiarity with Agile development methodologies and an understanding of Python. The real day to day: designing and implementing software solutions for the IoT platform, turning functional and technical requirements into detailed architecture and design, building scalable and high performing systems, architecting data driven solutions, writing documented and testable code, troubleshooting and debugging complex production issues, and applying software development best practices. Location and setup: Netradyne states this explicitly, which is unusually clear. Employment type is full time, the work model is on site, and the shift is general shift, 5 days a week. The office is HM Tech Park, Whitefield, Bangalore, and the posting notes potential for some work flexibility. Treat this as a 5 day in office role in Whitefield unless the recruiter tells you otherwise. Honest fit guidance: this is one of the few roles on today's board that a first job engineer can actually clear, but the C and C++ requirement is real and the work is embedded, not web or application development. If your experience is in Java or Python web stacks, the title will fit and the skills will not. Netradyne also publishes a recruitment fraud warning: official communication comes only from addresses ending in netradyne.com or us-greenhouse-mail.io, the company never asks for payment for equipment, and it does not use agencies that charge candidates a fee. The posting does not publish an interview process.
What the posting asks for: 1 to 3 years of L2 technical support experience with enterprise SaaS platforms in a customer facing role, AWS cloud preferred. Mindtickle also wants a track record handling technical issues in production while supporting distributed systems, experience supporting a multi tenant SaaS product including its integrations and configuration management, and hands on troubleshooting of AI powered features with the ability to separate model issues from data, configuration or system level failures. Knowledge of authentication and enterprise integrations is required, specifically SSO protocols such as SAML, OAuth 2.0 and OpenID Connect. The real day to day, in three parts. Operational support: responding quickly to customer queries, providing workarounds while permanent fixes are built, owning tickets to SLA, acting as an escalation point, and working across Product, Engineering, Quality Engineering and DevOps to kill recurring issues. Technical investigation: reproducing and debugging problems across backend services, APIs, data flows, UI behaviour and AI components, capturing browser logs, HAR files and network traces, analysing AI decision paths and validating model outputs for drift or anomalies, and running structured impact and severity analysis before escalating. The named tooling is Zipy, Datadog, SumoLogic, FullStory, Mixpanel and Metabase. Knowledge work: building runbooks, playbooks and troubleshooting guides, converting solved issues into product and documentation improvements, and running deep dive sessions and post incident walkthroughs. Automation: writing Bash, Python and SQL to automate log extraction, data analysis and issue replication, and contributing to AI assisted troubleshooting tooling. Location and setup: Pune, Maharashtra. The posting does not state office days. Honest fit guidance: this is support engineering, not product engineering, so you will be measured on resolution and SLA rather than shipped features. In exchange you get real depth in distributed systems debugging and unusually direct access to Engineering and Product. Mindtickle itself frames it as an L2 role with more influence than most. Good fit if you enjoy diagnosis and customer contact, poor fit if you want to be writing product code most of the week. The posting does not publish an interview process.
What the posting asks for: 2 to 5 years of professional software engineering experience, experience with a modern programming language such as Python, Go or Rust, excellent communication, and comfort with modern infrastructure and delivery systems including containerised applications, Kubernetes and CI/CD tooling such as Drone.io or similar. MongoDB describes the ideal candidate as collaborative, detail oriented and genuinely interested in making software usable. Nice to have, called the bonus round in the posting: experience building full stack applications from front end UIs through backend API handlers to database migrations, and knowledge of Next.js, FastAPI or React. The real day to day: building and maintaining internal tools and platforms that improve workflows and efficiency, writing clean and maintainable code to fix bugs and add features, and working with other engineers and teams to prioritise and deliver. MongoDB publishes its success measures for the role, which is rare and worth reading as the actual expectation. Within three months you should be familiar with internal platforms and workflows and contributing meaningfully to projects in flight, and should have reduced manual friction in internal processes by delivering working features or improvements. Within six months you should have implemented tooling or enhancements that measurably improve internal engineering efficiency and productivity. Location and setup: Gurugram, and the posting is explicit that MongoDB is looking for candidates based in Gurugram for its hybrid working model. Honest fit guidance: internal tooling is sometimes treated as lower status than customer facing product work, and it is worth being clear eyed that your users are colleagues rather than customers. The upside is a new team, early influence over how it works, and a short path from writing something to seeing it used. If you want to work on the MongoDB database engine, this is not that role.
What the posting asks for: 2 to 5 years as a Software Engineer or Python Developer, strong Python with the ability to pick up new frameworks and libraries quickly, hands on SQL for querying and data manipulation, experience with data visualisation and plotting tools such as Matplotlib, Seaborn or Plotly, familiarity with alerting and monitoring tools, and a solid grounding in data structures, algorithms and object oriented programming. Graviton also asks for strong analytical thinking and attention to detail. The real day to day: designing and developing efficient Python scripts for data analysis and automation, building accurate data visualisations that support decision making, implementing and maintaining alerting tools that monitor data workflows and systems, working with other teams to gather requirements, and continuously optimising data processing pipelines for scalability and performance. Location and setup: Gurugram, Haryana, on site. Graviton describes a cubicle free office and a deliberately non hierarchical culture. Published benefits are competitive compensation, 6 weeks of paid vacation, catered breakfast and lunch, a fully stocked kitchen, monthly after work parties and an international team outing. Honest fit guidance: this is a data and tooling engineering role inside a trading firm, not a quant researcher or trader seat, so do not apply expecting to build alpha models. What you get instead is a high signal engineering environment, exposure to financial market data at scale, and a bar set by a firm that says openly it insists on hiring the very best. Graviton has three separate openings on today's board (this one, HPC Engineer at 2 to 3 years, and Application Reliability Engineer at up to 2 years), all in Gurugram and all distinct teams, so compare the three before applying rather than sending the same application to each. The posting does not publish an interview process.
What the posting asks for: Netradyne states the experience range as 2 to 5 years, and separately asks for 2 to 4 years in SDET or quality engineering roles. It publishes a skills table: Python at expert level and shell scripting in Bash or Zsh at intermediate or above are required, while SQL and PostgreSQL at intermediate level and Jenkins or similar CI/CD tooling at intermediate level are listed as desired. The real day to day: designing and executing end to end test plans that validate hardware and software modules of IoT devices, including firmware behaviour, sensor integrations and communication interfaces. Developing and maintaining automated test scripts that verify device function across real operating conditions, edge cases and failure scenarios. Building tooling that simulates real world device conditions so resilience can be verified without relying solely on physical test environments. Monitoring and querying large scale device datasets and telemetry logs to detect anomalies, regressions and performance degradation. Contributing to the architecture of the in house test automation framework so it stays extensible and reusable across teams. Integrating automated tests into CI/CD pipelines for fast feedback on every build. Identifying and triaging defects with clear reproduction steps and root cause analysis. Championing quality practices including code review, coverage standards and shift left testing. You would work directly with hardware engineers, firmware developers, backend engineers and product teams, on the Engineering Quality team in Bangalore. Location and setup: Bangalore. This posting does not state office days, though Netradyne's other Bangalore openings specify on site, general shift, 5 days a week at HM Tech Park, Whitefield, so ask. Honest fit guidance: the Senior label and the 2 to 5 year range are a good illustration of why the years matter more than the title. This is hands on test engineering with real hardware in the loop, which is a different skill set from pure web QA automation. If you want to move from manual or UI testing into device and telemetry work, it is a strong bridge. The posting does not publish an interview process.
What the posting asks for: the ideal candidate has 2 to 3 years of experience, with a degree in EE, CS or CSE. Graviton adds that Bachelor's graduates will also be considered given an exceptional background and prior experience in the HPC field. Required skills are programming in Python or Bash, a good working understanding of Linux at user level, experience with large scale distributed HPC systems, and an understanding of large scale batch processing systems such as PBS Pro, Torque or Slurm along with approaches to efficient scheduling. HPC system monitoring and automation tools are preferred. The responsibilities as listed: hands on experience deploying high performance clusters, working with cluster management tools, exposure to multiprocessor and multithreading concepts, working on Linux, and handling testing, user support, troubleshooting and root cause analysis of issues. Experience with parallel filesystem environments is marked optional. Location and setup: Gurugram, on site. Published benefits are competitive compensation, an annual international team outing, fully covered commuting expenses, health insurance, catered breakfast and lunch, a stocked kitchen, 4 weeks of annual leave plus market holidays, gym and sports club memberships, and regular social events. Honest fit guidance: this is infrastructure and systems work, not trading or model development, and the day to day is closer to a research computing role at a university or national lab than to a software product team. That makes it an unusual and quite specific opening. The explicit note that strong Bachelor's graduates will be considered is worth taking seriously if you have real cluster experience from an academic or internship setting, since HPC exposure is genuinely hard to come by in India outside a handful of employers. Note this is Graviton's third open role today alongside a Python engineer role and an application reliability role. The posting does not publish an interview process.
What the posting asks for: a Bachelor's or Master's degree in Computer Science or a related field, and 3 to 6 years of Python based data or backend engineering. Required alongside that are strong programming fundamentals in data structures, algorithms and object oriented design, experience with AWS services such as Kinesis, SQS or Lambda, experience building and managing data pipelines and workflows with Airflow DAGs, a good understanding of data modelling and both relational and NoSQL databases, experience with Docker and Kubernetes, hands on GitHub and CI/CD tooling such as Jenkins, and strong Linux fundamentals and debugging skills. Preferred, not required: prior experience at a product or SaaS company, streaming and event driven architectures, exposure to NoSQL stores such as MongoDB or Cassandra, a basic understanding of ML pipelines, and familiarity with modern AI concepts such as RAG, AI agents and prompting. The real day to day: building and maintaining scalable pipelines for real time and batch processing on Kinesis and SQS based systems, developing data platforms that support ML feature generation, training and validation, optimising pipeline performance and reliability at high volume, writing backend components and services for data processing, deploying and troubleshooting production data systems, working with distributed systems in Docker and Kubernetes on EKS, partnering with Data Science and ML teams to productionise AI solutions, and following engineering practices around code quality, testing and CI/CD. The posting also lists working with AI agents to solve data engineering problems. Location and setup: Bangalore. This posting does not state office days, but Netradyne's other Bangalore roles specify on site, general shift, 5 days a week at HM Tech Park, Whitefield, so assume in office and confirm. Honest fit guidance: strong choice if you want data engineering that stays close to production ML rather than to BI and reporting, and if you are comfortable that a good share of the week is backend service work and on call style troubleshooting. Netradyne has three separate openings on today's list across different teams, so pick the one that matches rather than applying to all three.
What the posting asks for: extensive and expert programming experience in at least one general purpose language such as Java, C or C plus plus, and the ability to write maintainable, scalable, unit tested code. Also required are experience with multithreading and concurrency programming, experience building highly scalable business applications involving complex business flows and large data volumes, strong object oriented design skills with knowledge of design patterns and a genuine interest in designing clean module and class level interfaces, excellent coding ability so a design converts fluently into code, knowledge of test driven development, a good understanding of databases such as MySQL and NoSQL stores such as HBase, Elasticsearch and Aerospike, and full lifecycle development experience on Linux. PhonePe also asks for experience in a startup environment with high levels of ownership. The title states 3 to 5 years. The real day to day: building robust and scalable web based applications, building abstractions and contracts with separation of concerns at larger scope, driving problem solving for high level business and technical problems, doing high level design with guidance including functional modelling and module breakdown, making incremental architecture changes and analysing their impact, performance tuning large scale distributed systems, working closely with a Product Manager to turn features into capability views and leading execution of medium sized projects, tracking the impact of what ships and iterating, and mentoring junior engineers while breaking execution into phases to make delivery predictable. Location and setup: Pune. The posting does not state office days. Honest fit guidance: PhonePe describes a culture where you own your work end to end from day one and where teams often build frameworks from scratch, which is a real signal about pace and expectations. The payments domain means correctness and availability matter more than shipping speed, and the volumes quoted are not marketing: 330 million transactions a day is a genuinely demanding backend environment. Note this is the Pune opening, and PhonePe also has a Bangalore SRE role on today's board, which is a different team and a different skill set.
What the posting asks for: 3 or more years in a DevOps, SRE or Infrastructure Engineering role. Sarvam marks two requirements non negotiable: strong hands on production Kubernetes covering deployments, Helm charts, HPAs, CronJobs, node affinity, resource management and debugging pod failures, and proficiency with at least one major cloud among Azure, GCP or AWS covering managed Kubernetes, container registries, blob storage, secrets vaults and IAM. Beyond those it asks for experience building and maintaining CI/CD pipelines with container builds, automated testing gates, multi environment promotion and deployment automation, solid containerisation including production Dockerfiles, multi stage builds and image optimisation, experience with monitoring and observability stacks such as Prometheus, Grafana, OpenTelemetry or Sentry, strong Linux systems knowledge across networking, process management, storage and system level debugging, scripting in Python or Bash, a good understanding of networking including DNS, load balancing, ingress controllers, TLS termination and CDN configuration, experience with secrets management patterns such as External Secrets Operator or Sealed Secrets, and familiarity with Redis or similar in memory stores for queues and pub sub. The real day to day: operating production Kubernetes with multi role deployments across API servers, task schedulers, per stage workers and WebSocket servers. Building and optimising CI/CD with staged rollouts across QA, staging and production. Maintaining Helm charts, shared module dependencies and environment specific value overlays. Implementing metrics, dashboards, error tracking and distributed tracing. Operating blob storage with CDN for media delivery, ingress, secrets and IAM. Coordinating multi cloud deployments and artifact management for Docker images and internal Python packages. Running vault to cluster secret sync. Optimising async task queues including dead letter handling and stuck message recovery. Monitoring database query health, connection pooling and backup and recovery. Building developer productivity tooling and local dev environments. Owning incident response including runbooks, alerting rules and post mortems. Driving cost optimisation through right sizing, autoscaling policies and storage lifecycle management. Location and setup: Bengaluru. The posting does not state office days. Honest fit guidance: the workload is ML heavy and GPU backed, which is meaningfully harder to operate than a standard web stack, and the posting is honest that failures cascade across pipeline stages. Good fit if you want infrastructure work at a company where the infrastructure is the hard part. Sarvam also has a Studio backend role open today at 4 to 6 years, which is the same platform from the application side.
What the posting asks for, listed by Zscaler as minimum qualifications: demonstrated curiosity and active use of AI tools with a history of integrating new technology into daily workflows, 3 or more years of Java in a highly distributed and enterprise scale environment with experience in Kafka, Druid and Elasticsearch, experience being on call and handling cloud incidents including writing root cause analyses, working knowledge of cloud infrastructure services on AWS or Azure, and a Bachelor's or Master's in Computer Science or equivalent experience. Preferred qualifications, described as what will make you stand out: experience building full CI/CD systems using Kubernetes and web service frameworks, experience building reliable and extensible data tiers for large scale web services with Postgres and Redis, and experience with identity and access management systems such as Okta, SAML protocols and OAuth. The real day to day: understanding how to build and operate high scale systems, providing service and product wide architectural guidance and driving technical decisions, establishing and enforcing best practices for coding, testing, observability and CI/CD to keep services production ready, and driving cross team collaboration on performance optimisation, reliability improvements and adoption of new technology to accelerate feature velocity. Zscaler also publishes a success profile: comfort with ambiguity and building the path as you walk it, acting like an owner with a bias for action, running toward hard problems, and being a high trust collaborator who puts team success first. Location and setup: the posting lists the location as India and is tagged hybrid, reporting to a Senior Director of Software Engineering. The location field on this posting reads "India, Update Location", so confirm the specific city with the recruiter before applying. Honest fit guidance: the mismatch between the Senior title and the 3 year minimum is worth acting on, because engineers at 3 to 4 years often filter out anything labelled Senior and would never see this. The AI tooling requirement is listed first among the minimum qualifications, not as a nice to have, which tells you something about how the team expects to work. Being on call is explicitly part of the job.
What the posting asks for: 3 or more years of industry experience building large scale NLP and NLU systems, with recent hands on work in LLMs and LLM powered paradigms including agentic AI. The real day to day: designing and developing state of the art LLM powered AI capabilities and agentic or multi agent systems end to end, from idea through to production, in a fast moving startup environment. Working with current tooling across machine learning, deep learning and natural language processing. Building and maintaining highly scalable production systems that power the AI capabilities in the product. Optimising ML models and processing pipelines for performance, cost effectiveness and scale. Mentoring more junior engineers and influencing peers and stakeholders. Collaborating across engineering, product, customer facing teams and customers. What the team offers beyond the work: Observe.AI states that you will have the opportunity to publish at top conferences and to influence the company's product and platform strategy, and describes the ML team as working on multi agent systems, LLMs and applied research turned into production systems handling millions of interactions daily. Location and setup: Bengaluru. The posting does not state office days. Honest fit guidance: the posting says plainly that it wants someone who is "truly an engineer at heart", and the responsibilities back that up: this is applied ML with a heavy production systems component, not a research seat. If your experience is fine tuning and evaluation without owning the serving path, expect the scale and reliability parts to be the stretch. At 3 or more years it is one of the more accessible senior ML openings on the board, and it sits in the same company as an SDE III backend role also listed today, which is a different team.
What the posting asks for: Twilio states it is hiring for multiple positions at either a Senior or a Staff level under this one listing. The Senior level asks for 3 or more years of professional software development experience, ideally full stack. The Staff level asks for 5 or more years of professional full stack software development experience. Apply against the level that matches you rather than assuming the higher bar applies. The real day to day differs by level, and Twilio spells both out. At the Senior level: developing, testing and deploying code for prototypes and new product features, working with the team to solve technical problems and improve solution design, taking part in code reviews, documentation and knowledge sharing, experimenting with modern tools, frameworks and emerging technology, and adapting to changing requirements while contributing to process improvement. Twilio calls this a growth role, suited to someone eager to learn in a fast paced and entrepreneurial environment. At the Staff level: designing, developing and implementing prototypes and production ready solutions, experimenting with AI, machine learning and emerging technology alongside the team, contributing to engineering best practice through code review, communicating progress and technical concepts to stakeholders, and adapting quickly to feedback and changing requirements. Location and setup: remote within India. Twilio describes a dedication to remote first work and a culture of global connection, and this is genuinely a distributed role rather than a hybrid one. Two things worth knowing before you apply. Twilio states openly that it uses AI to help make its hiring process efficient, while adding that every hiring decision is made by a person. And Twilio's remote India postings have historically been restricted to a subset of Indian states, so confirm your state is eligible with the recruiter rather than assuming all of India qualifies. Honest fit guidance: incubation work means ambiguity, short cycles and a real chance that something you build does not ship, which suits some engineers and frustrates others. The compensating benefit is breadth and exposure to new technology early. Twilio also has a Staff Business Intelligence Engineer role open remotely today at 7 or more years, which is a different team on the data side.
What the posting asks for: a Bachelor's degree in Computer Science, Engineering or a related field, 3 or more years working with PySpark and SQL, 2 or more years building and maintaining data pipelines on Amazon EMR or Amazon Glue, 2 or more years of data modelling and end user querying with Amazon Redshift or Snowflake plus Athena and Presto, and 1 or more years building and maintaining pipeline orchestration with Airflow. It also asks for strong problem solving and troubleshooting, excellent communication and collaboration, and the ability to work both independently and in a team. Preferred, not required: an AWS Data Analytics Specialty certification and experience with Agile development. The real day to day: building and maintaining production data pipelines on EMR or Glue, designing data models and end user querying on Redshift or Snowflake, Athena and Presto, building pipeline orchestration with Airflow, working with customer and internal teams to understand data needs and design solutions, troubleshooting and optimising pipelines and models until they hold under real load, writing and maintaining PySpark and SQL for extract, transform and load work, documenting and communicating technical decisions to both technical and non technical audiences since customers sign off on what ships, and tracking new AWS data technology to judge whether it belongs in the systems Mactores runs. Location and setup: the listing is tagged Mumbai, Maharashtra, but the posting body states plainly that the role is fully remote. It also describes a forward deployed model where senior engineers embed with the customer's team and carry the delivery commitment personally against fixed dates, with Mactores absorbing overage cost for delays inside its control. Confirm the remote arrangement and any client site travel expectation with the recruiter, since embedded consulting and fully remote can pull in different directions. Honest fit guidance: this is consulting delivery work, so you will be working against customer commitments and sign offs rather than an internal roadmap, and the posting is candid that the culture is measured by what ships. Note also that Mactores lists a separate freelancer variant of this same role, so check which one you are applying to. The 3 year floor against a Senior title makes this reachable earlier than the name suggests.
What the posting asks for: 4 to 6 years in backend engineering with a focus on building and operating production services at scale. Sarvam marks Python and production FastAPI or similar async web service experience as non negotiable. Beyond that it asks for a deep understanding of async programming including asyncio, concurrent execution patterns and designing for high throughput, experience with distributed task systems covering task queues such as Celery, message brokers and fault tolerant job orchestration, hands on PostgreSQL with an async ORM such as SQLAlchemy including query optimisation, schema design and migrations, familiarity with audio and media processing using FFmpeg, common audio formats and libraries such as soundfile or librosa, experience integrating ML models into production whether API based over REST or gRPC or local inference with PyTorch or ONNX Runtime, experience building reusable libraries or SDKs with clean APIs and backward compatibility, proficiency with Docker, Kubernetes, Helm and at least one major cloud, and strong testing discipline including mocking external services and maintaining CI/CD. Bonus points: prior experience with speech or NLP systems such as ASR, TTS or machine translation. The real day to day, across three areas. Service and infrastructure: designing production FastAPI services for dubbing and live translation with multi stage task orchestration, rate limited scheduling and backpressure controls, building distributed worker architectures with independent scaling per pipeline stage and automatic recovery of stuck tasks, owning the async ORM data layer and migrations on PostgreSQL, implementing WebSocket based job tracking and streaming audio pipelines, and managing Kubernetes deployments including Helm charts, secrets, ingress and multi role images. ML pipeline and library: extending the core dubbing library across audio extraction, voice activity detection, speech recognition, translation, quality control, text to speech and video stitching, integrating and optimising ML model serving for both remote inference and local inference, building quality control orchestration including automated scoring, tempo analysis and pronunciation verification, and maintaining LLM integration layers across multiple provider backends. Platform SDK: maintaining the shared Studio SDK with reusable FastAPI middleware and routers for authentication, billing, workspace isolation and input validation. Location and setup: Bengaluru. The posting does not state office days. Honest fit guidance: the media and audio processing element is a genuine specialisation, and the posting is explicit that FastAPI and async depth are not negotiable. If your backend experience is synchronous request and response web services, this will be a real jump. Sarvam also has a Studio DevOps role open today at 3 or more years, which is the same platform from the infrastructure side.
What the posting asks for: a minimum of 4 to 7 years of strong hands on Linux and Unix system administration, including TCP/IP, DNS and load balancers, plus expertise in managing and scaling infrastructure. The real day to day: troubleshooting issues across the entire stack covering hardware, software, application and network. Improving the reliability and performance of distributed systems and containerised deployments. Diagnosing complex distributed systems handling millions of queries per second. Working in a heavily command line driven environment that requires strong Linux understanding. Participating in an on call rotation. Designing, building and maintaining the core infrastructure that lets PhonePe scale to hundreds of thousands of concurrent users. Taking part in analysis and system improvement planning. Driving performance testing, capacity planning and high availability practices. Owning implementations of new technology with proper testing and documentation. Proactively monitoring and solving issues that could affect infrastructure. Onboarding new team members and getting them production ready. Location and setup: Bangalore. The posting does not state office days. Honest fit guidance: the on call rotation is stated in the posting rather than buried, and in a payments business an incident at 2am is a real incident, so weigh that honestly. PhonePe describes a culture where you own your work end to end from day one and teams frequently build frameworks from scratch, which suggests genuine autonomy but also limited hand holding. Worth noting PhonePe has several similarly titled SRE openings live, including SRE 3 and a big data focused SRE at 7 or more years, so check you are applying to the level that fits. This is the Bangalore infrastructure role; PhonePe's Pune backend role on today's board is a different team and skill set.
What the posting asks for: 4 or more years of professional experience in engineering or technical consulting. The role is built on deep Kubernetes knowledge, since Nirmata expects you to go deep in Kubernetes and in Nirmata's own solutions, including using its AI capabilities against customer problems. The real day to day, as Nirmata lists it. Custom engineering and proof of value: building working solutions against live production systems to demonstrate provable return on investment tied to the customer's own data and environment. Cloud native and AI expertise: being the expert who goes deep on Kubernetes as the orchestrator for both software and AI workloads. Enterprise implementation: verifying and implementing detailed technical designs that address complex customer problems and drive platform adoption. Technical leadership: leading customer initiatives by understanding the business implications and architecting for operational, integration and scaling requirements. Operational excellence: providing design and operational solutions for enterprise container adoption, including building the necessary tools and automation. Research and development feedback: gathering field insight and giving Engineering clear product feedback grounded in real customer requirements. Customer advocacy: managing technical escalations, educating customers and documenting best practice. Value realisation: helping customers define, capture and document the financial value the platform delivers. Location and setup: Bangalore. The posting does not state office days. Honest fit guidance: Nirmata says outright that this is unlike a traditional customer success role, and the responsibilities support that, since you are building against live production systems rather than running adoption checklists. The trade off is that your work is measured in customer outcomes and renewals rather than shipped features, and you will spend real time in meetings and escalations. Good fit if you have Kubernetes depth and want to use it in front of customers. Poor fit if you want to be heads down in a codebase. Nirmata is also a much smaller company than most on this list, which usually means broader scope and less structure.
What the posting asks for: 5 to 9 years of experience building large scale products. The real day to day: contributing to building and deploying AI agents for customer service in the form of voice agents, chat agents and copilots at enterprise scale. Owning the full application lifecycle through design, coding, testing, deployment and debugging with a high quality bar. Working with product and design to translate the product roadmap into a clear technical roadmap. Developing reusable code, frameworks and libraries to speed up development and keep projects consistent. Optimising applications for speed, scalability and reliability by proactively addressing bottlenecks and performance issues. Implementing security measures and data protection practices to safeguard applications and sensitive customer data. Designing and managing scalable data storage that stays efficient, reliable and maintainable. Building and scaling efficient data pipelines that process large volumes accurately. Reviewing others' work as part of the team's quality process. Location and setup: Bengaluru. The posting does not state office days. Honest fit guidance: this is backend platform engineering supporting AI products, not machine learning engineering, so the daily work is distributed systems, data pipelines and API design rather than models and evaluation. If you want to move closer to AI without retraining as an ML engineer, that distinction works in your favour. Observe.AI describes a culture that prizes speed and ownership, which usually means less process and more direct responsibility. Note Observe.AI also has a Senior ML Engineer NLP role on today's board at 3 or more years, which is the model side of the same product, so pick according to which half of the system you want to own.
What the posting asks for: 5 or more years of professional experience in machine learning and software engineering. Coinbase states the level directly, hiring an IC5 Machine Learning Engineer. The real day to day: architecting and deploying the orchestration layer that manages state transitions, context sharing and intent routing across vendor and internal LLM frameworks in a distributed conversational environment. Building production grade Python services that connect ML and AI research to reliable, measurable customer facing products. Leading end to end execution on complex ML initiatives, managing priorities, technical trade offs and cross functional dependencies from design through delivery. Establishing best practice for system design, coding standards and AI and ML development workflows across the team. Mentoring engineers on architectural integrity and modern AI and ML patterns. Running design reviews. The team context: CX Intelligence sits inside Coinbase's Enterprise Applications and Architecture organisation and owns the multi agent platform powering Coinbase chat, the Help Center and agent tooling, working with Conversation Design, CX and other engineering teams to deliver secure and compliant AI powered support. Location and setup, and this matters: the role is remote within India, but Coinbase states plainly that it is remote first, not remote only, and that you should expect to gather quarterly for in person working sessions it calls surges. If travel every quarter is a problem, factor that in now rather than at offer stage. Coinbase is also unusually blunt about culture in the posting itself, saying the bar is high and the environment is intense. Honest fit guidance: the interesting engineering here is the hand off logic between different LLM frameworks and between AI and human agents, which is a genuinely hard and current problem. It is applied ML with a heavy production systems and architecture component, so it suits someone who has shipped and operated ML services rather than someone whose experience is model training alone. Coinbase has three remote India roles on today's board across different teams.
What the posting asks for: 5 or more years in IT engineering, automation or systems engineering, with demonstrated ownership of architecture decisions, engineering standards or platform level systems that others build on. Also required are deep expertise building and maintaining complex automations using n8n, Airflow, Temporal, Jira Automation or Workato, paired with strong Git based development workflows including branching, CI/CD and code review, and working knowledge of Okta, Slack API and Google Workspace administration sufficient to design against them. The real day to day: owning the technical architecture of IT Tooling automations and driving design decisions on system structure, integration patterns and tooling across n8n, Airflow, Temporal and Jira. Establishing architecture standards and code review practices that raise the team's engineering bar. Leading as technical decision maker on the most complex, highest impact automation projects from discovery through production. Partnering with Security, Corporate Engineering and Identity and Access Management to clear technical blockers and representing the team in cross functional architecture discussions. Building shared frameworks and reusable components that reduce single points of failure. Producing architecture documentation and decision records so the team scales without depending on one person. Managing your own workload with high independence, turning loosely scoped problems into production ready specifications. Location and setup: remote within India. As with Coinbase's other openings, the company states it is remote first but not remote only, and that you should expect quarterly in person working sessions called surges. The team partners with regional IT groups across Asia Pacific, Europe and the Americas, so some schedule overlap across time zones is likely. Honest fit guidance: be clear about what this is. It is internal IT automation engineering, not product engineering, and your users are Coinbase employees. That is a real career distinction and some engineers will not want it. What it offers in exchange is genuine architectural ownership at 5 years, a modern automation stack, and a remote role at a large employer. If you have been doing IT operations and want to move toward platform engineering, this is a credible bridge. If you want to build customer facing product, look at Coinbase's other two openings on today's board instead.
What the posting asks for: a minimum of 5 or more years of relevant experience as a Data Scientist, preferably in a consulting role. Alongside that Databricks asks for experience building GenAI applications including RAG, multi agent systems, Text2SQL and fine tuning with tools such as HuggingFace, LangChain and DSPy, expertise deploying production grade GenAI applications including evaluation and optimisation, extensive hands on industry data science experience with common tooling such as pandas, scikit learn and PyTorch, experience building production grade machine learning deployments on AWS, Azure or GCP, a graduate degree in a quantitative discipline such as Computer Science, Engineering, Statistics or Operations Research or equivalent practical experience, and the ability to explain technical concepts to both technical and non technical audiences. Preferred, not required: experience using the Databricks Intelligence Platform and Apache Spark to process large scale distributed datasets. The real day to day: developing GenAI solutions that incorporate techniques from Databricks' own Mosaic AI research to solve customer problems. Owning production rollouts of both consumer facing and internal GenAI applications. Serving as a trusted technical advisor to customers across a variety of domains. Presenting at conferences such as the Data and AI Summit and being recognised as a thought leader internally and externally. Collaborating with product and engineering teams to influence priorities and shape the roadmap. Location and setup: the posting states the role can be remote, and the listing specifies India. Honest fit guidance: this is a customer facing professional services role, so a real share of your week goes to customer meetings, discovery and advisory work rather than heads down building. Databricks describes the team as an ensemble that looks for individuals with strong unique specialisations, which suggests depth in one area matters more than breadth. The graduate degree requirement is stated, though Databricks allows equivalent practical experience, so do not self reject on that alone if your production GenAI record is strong. The conference speaking expectation is unusual and worth taking at face value: visibility is part of the job.
What the posting asks for, and read this carefully because the numbers stack: 5 or more years of professional experience overall, and separately 3 or more years working in data engineering, business intelligence or a similar role. The effective floor is 5 years, not 3. Also required are proficiency using AI coding tools such as Claude Code, Codex or Cursor across the full software development lifecycle from design and code generation through testing, monitoring and release, proficiency in Python or Java, 3 or more years with ETL orchestration and workflow management tools such as Airflow, Flink, Oozie or Azkaban on AWS or GCP, expert level database fundamentals, SQL and distributed computing, 3 or more years with the distributed data ecosystem including Spark, Hive, Druid and Presto plus streaming technologies such as Kafka or Flink, experience with Snowflake, Redshift, PostgreSQL or other database platforms, knowledge of reporting tools such as Tableau, Superset and Looker, and strong communication with both technical and non technical teams. The real day to day: working with business partners and stakeholders to understand data requirements, working with engineering, product teams and third parties to collect the required data, designing and implementing large scale high volume high performance data models and pipelines for the data lake and warehouse, developing data quality checks and monitoring routines, improving the reliability and scalability of ETL processes, managing a portfolio of data products that deliver trustworthy data, and helping onboard and support engineers joining the team. Location and setup: Hyderabad, India. The posting states that you must be located near one of DoorDash's engineering hubs, so this is not a remote role despite being on a large distributed company's board. Honest fit guidance: the explicit requirement for proficiency with AI coding tools is worth noting, since it is listed as a requirement rather than a nice to have and names specific products. This is a good example of why reading the experience sentence by hand matters: an automated parser would report this role as 3 years because that number appears three times, when the actual floor is 5. Strong choice if you want data engineering at genuine consumer scale, and DoorDash's data organisation is explicitly the foundation for company decision making rather than a reporting function.
What the posting asks for: 5 to 7 years of experience in a customer account facing role. Datadog also wants a strong communicator with excellent attention to detail, someone motivated by building long lasting relationships, experience negotiating contract terms and overcoming pricing objections without direct guidance for upsell and cross sell, and a proven track record of hitting account expansion targets measured by growth and retention of a portfolio. The real day to day: partnering with the sales team for a smooth transition and onboarding, proactively building customer relationships to create mutual trust, carrying out the full sales cycle for growth opportunities inside existing accounts, advising customers so they use Datadog effectively, monitoring usage trends to uncover renewal risk and promote adoption, and collaborating across Datadog's Support, Product, Finance and Legal teams. What Datadog offers around the role: it publishes a structured onboarding programme and sales training in MEDDIC and Command of the Message, which is a real signal that the methodology is taught rather than assumed. Location and setup: Bangalore, India. Datadog states its position openly, saying it values office culture and operates as a hybrid workplace. Ask what hybrid means in days for this team. Honest fit guidance: be clear about what this role is. Despite sitting on a technical products board, it is a commercial customer success role carrying expansion targets, not an engineering or solutions engineering job. If you want the technical version, Datadog's Technical Account Manager 2 role is also on today's board and asks for hands on cloud, scripting and CI/CD skills instead. Datadog adds a note worth repeating, that not everyone will meet all the qualifications on day one and it encourages applying anyway if you are passionate about the technology.
What the posting asks for: 6 or more years of data engineering experience, with at least 2 of those in a senior or lead capacity. The real day to day: owning and evolving the data platform across StarRocks for OLAP, Apache Hudi for the data lake, Trino, Spark and Apache Ranger, keeping performance, reliability and security intact at scale. Building the next generation AI optimised data layer, meaning clean structured datasets that power natural language querying and AI add on features for HackerRank for Work customers. Owning in product data features including exports, insights dashboards, interview analytics and the self serve custom reports interface. Enabling self service pipelines for internal teams across AI platform, analytics and go to market, which reduces ad hoc data requests. Enforcing data security through access controls, Apache Ranger policies and confidence scoring guardrails on AI generated output. Leading technical design reviews and defining engineering standards for the data team. Partnering with product managers and business stakeholders to identify and scope AI enabled data use cases. Location and setup: hybrid in Bangalore, India. The posting does not state how many days. Honest fit guidance: HackerRank is unusually specific about where the platform stands, which is useful, because it tells you the painful migration is behind you and the work ahead is building features rather than firefighting legacy. The posting calls this a greenfield opportunity to shape the next phase of data at the company. Note the framing as a senior individual contributor at the heart of the data organisation: the Lead in the title means technical leadership and design authority, not people management, so it stays on this board. Good fit if you want platform ownership and direct line of sight from your work to revenue features. Less good if you want a large existing team around you, since the role reads as a small senior group with wide scope.
What the posting asks for: 7 or more years of experience in business intelligence, data analytics or a related field, with at least 2 of those in a staff or senior individual contributor role. The real day to day: owning and evolving Twilio's suite of business intelligence tools, driving governance, performance and long term roadmap decisions. Designing and building scalable, reusable dashboards and reports that surface actionable insight for stakeholders across legal, billing operations and other mission critical functions. Architecting and deploying agentic AI solutions that enable natural language querying, automated insight generation and self service analytics for non technical business partners. Collaborating with data engineers, business partners and AI and ML engineers to turn complex analytical requirements into reliable, well documented data products. Establishing and championing BI best practice including semantic layer design, metric definitions, data access governance and documentation standards. Partnering with business leaders to find opportunities where better data visibility changes decisions. Location and setup: remote within India. Twilio describes a dedication to remote first work and a strong culture of global connection, so this is a genuinely distributed role. One caveat: Twilio's remote India postings have historically been open only to a subset of Indian states, so confirm your state qualifies before you invest in the process. Twilio also states openly that it uses AI to help make its hiring process efficient, while adding that every hiring decision is made by a person. Honest fit guidance: this is a platform and strategy role rather than a report building one, and the agentic AI element is a real part of the brief rather than decoration, so experience with semantic layers and self service analytics architecture matters more than dashboard volume. The stakeholder set is heavily internal business functions including legal and billing operations, which means influence and documentation are as important as technical skill. Twilio also has a remote Senior or Staff Applied Research Software Engineer role on today's board at 3 or more years, which is a very different team.
What the posting asks for: 8 or more years of hands on software engineering experience with a demonstrated track record of the kind of platform ownership this role requires. Coinbase names the level explicitly as Staff. The real day to day: architecting and delivering foundational platform capabilities including tool registries, AI orchestration layers, risk based access automation, and the contribution model that lets product groups across Coinbase build on the platform safely and quickly. Driving the evolution of Control Center into an AI agent ready, headless operations platform by designing procedure constructs, agentic guardrails, human in the loop orchestration and evaluation frameworks so that both people and autonomous agents can carry out sensitive customer operations securely. Partnering with the Engineering Manager and product counterparts to define architectural roadmaps, author technical design documents, lead design reviews, break complex initiatives into deliverable milestones, and raise the engineering bar through code review and mentorship. Building and maintaining highly reliable platform services. Location and setup: remote within India. Coinbase states it is remote first but not remote only, and that you should expect quarterly in person working sessions it calls surges. Coinbase is also direct in the posting about culture, saying the bar is high and the environment is intense. Honest fit guidance: the substance here is unusually current, since designing guardrails and evaluation frameworks so AI agents can safely execute sensitive customer operations is a problem most companies are only starting to think about. The trade off is that this is an internal platform rather than a customer facing product, and the users are Coinbase specialists in compliance, legal and investigations. At Staff level the expectation is architectural leadership and mentorship rather than pure output, so the application should evidence decisions you owned, not just systems you worked on. This is one of three Coinbase remote India roles on today's board.
What the posting asks for: 8 or more years of software engineering experience with significant focus on building production systems, and separately a minimum of 2 or more years of hands on experience with AI integration architecture including using large language models in production workflows. Airbnb frames the ideal candidate as someone who takes ownership of systems and solutions, is eager to learn, and is enthusiastic about applying AI, specifically building new tools and integrations with Claude Code that extend what the team can do. The real day to day, as Airbnb describes a typical day: partnering with Finance and cross functional teams to turn their requirements into integrations, automations and reporting. Working alongside architects and other technical teams in design discussions and reviews. Migrating integrations from Oracle Cloud onto the in house platform. Pairing with and mentoring junior engineers and contractors through design reviews, architecture discussions and pair programming. Triaging and resolving issues across the integrations and infrastructure you support. Exploring the GenAI landscape, evaluating new models and techniques, and sharing what you learn. The stated responsibilities: owning the architecture, delivery and reliability of integrations and microservices in Java, Python and TypeScript, and extending the in house integration platform so technical teams across Airbnb can self serve. Location and setup: the listing reads Remote, Bangalore, India. Confirm with the recruiter whether that means fully remote from anywhere in India or remote while based in Bangalore, since the two are different and the wording does not settle it. Honest fit guidance: this is enterprise and internal platform engineering serving Finance, not consumer product work on the Airbnb marketplace, and that is a real distinction worth being honest with yourself about. What it offers is a large, well engineered internal platform, genuine AI adoption rather than a pilot, and a remote arrangement at a company with a strong engineering reputation. The Finance domain exposure is also a durable specialisation. If you want to work on search, pricing or the booking funnel, this is not that team.
⚠️ Years of experience: GitLab does not state a number anywhere in this posting, and we do not publish figures we cannot source. What GitLab does state is the level range in the title itself, Intermediate through Senior to Staff, so the entry point is the Intermediate rung rather than Staff. GitLab adds that it welcomes interest from candidates with varying levels of experience and that many successful candidates do not meet every requirement. Ask the recruiter where each level sits before you self reject. What the posting asks for: experience building instrumented, observable software systems. Knowledge of Git internals including its code and data structures, or practical experience operating Git servers. Experience writing and testing production code. GitLab also asks that you share its values and work in accordance with them, which it treats as a real requirement rather than boilerplate. The real day to day: taking part in architectural discussions and technical decisions on Git and Gitaly, helping drive implementation choices that improve correctness, performance and maintainability. Contributing features and fixes to upstream Git. Adapting Gitaly to make effective use of new and existing Git capabilities. Representing GitLab as a constructive participant in the open source ecosystem and building relationships that support ongoing collaboration with the Git community. Working across repository access, performance and long term maintainability. Location and setup: fully remote, with India among the listed locations alongside Canada, Poland, the United Kingdom and the United States. GitLab is one of the best known all remote companies, so remote here is the default operating model rather than an accommodation. Honest fit guidance: this is systems programming in C on one of the most widely used pieces of software in the world, and the requirement for Git internals knowledge or Git server operations experience is the real gate. Very few engineers have that, which cuts both ways: the pool is small, so genuine C and Git depth counts for a lot more than years on a CV. The upstream contribution element means your work is public and permanent, which is rare and valuable. Because GitLab spans three levels here, do not rule yourself out on seniority. Note also that a role open across five countries is competitive globally, not just in India.
⚠️ Years of experience: GitLab does not state a number in this posting, and we do not publish figures we cannot source. GitLab does say it welcomes interest from candidates with varying levels of experience and that many successful candidates do not meet every requirement. The framing that you are "eager to grow into customer facing technical leadership with strong mentorship and support" suggests this is not a first job but also not a principal level role. Ask the recruiter directly. What the posting asks for: experience providing technical consultancy and solution guidance through video calls and written channels, helping users or customers successfully adopt technical solutions. Familiarity with DevSecOps workflows and related tooling. The ability to manage multiple customer engagements in parallel, prioritise effectively and communicate status, risks and next steps clearly. An interest in supporting customers across Asia Pacific and Japan and adapting to different cultures, working styles and levels of technical maturity. GitLab states one hard requirement: you must be based in India with full working rights in India. The real day to day: providing on demand technical consultancy and solution guidance over Zoom and in writing, helping customers solve day to day issues and design and implement GitLab solutions for their DevSecOps workflows. Delivering workshops, demos and best practice guidance across the Asia Pacific and Japan region. Working with Account Executives and Renewals Managers to align technical recommendations with customer goals and support renewals and expansion by showing outcomes. Managing multiple engagements in parallel and keeping implementations on track. Contributing documentation and enablement content back to the wider team. Mentoring team members and customers through complex technical challenges. Location and setup: fully remote within India, and GitLab is explicit that this role suits someone who thrives in a remote, asynchronous environment. GitLab is an all remote company, so this is the default way the whole organisation works rather than an exception made for one role. Supporting the Asia Pacific and Japan region means your hours align reasonably well with India, unlike customer roles covering the Americas. Honest fit guidance: this is the technical end of customer success, closer to solutions engineering than to account management, and DevSecOps familiarity is the real requirement. It suits someone who enjoys explaining and unblocking as much as building. The renewals and expansion element means commercial outcomes are part of how the role is judged, so it is not purely technical. GitLab also has a remote backend engineering role on today's board on the Git and Gitaly team.
⚠️ Years of experience: Datadog does not state a number in this posting, and we do not publish figures we cannot source. It does ask for previous experience working as a TAM supporting mid market or enterprise customers in the cloud space, which implies you have done the job before rather than entering it fresh. Ask the recruiter what band the "2" in the title corresponds to. What the posting asks for: a solid technical grounding with hands on IT operations experience. Confident hands on experience with AWS, Azure or GCP. Comfort with scripting languages such as Python, JavaScript, Ruby, Perl, Go or PHP, or configuration tooling such as Chef or Puppet. Skill with CI/CD tools such as Jenkins or GitLab. Knowledge of containerisation tools such as Docker, Kubernetes or Rancher. Previous experience as a TAM supporting mid market or enterprise cloud customers. Experience working across Sales, Support and Engineering. Experience using Datadog or other cloud monitoring tools. One requirement that is easy to miss and hard to undo: the posting asks that you be able to travel by road, rail or air up to 30% of the time. That is roughly one week in three. If travel at that level does not work for you, this is the wrong role regardless of technical fit. The real day to day: advising on technical support and product adoption for customers across pre sales, post sales and renewal processes. Analysing the customer's IT operations environment regularly and recommending changes that maximise the value they get from Datadog. Acting as the customer's advocate by knowing their goals and use cases, then suggesting process changes, product adoption, configuration and additional features. Preparing for and taking part in monthly and quarterly business reviews with customers. Working with Datadog's product management, engineering and technical services teams to help identify new features and products. Continuously evolving best practice for technical product adoption. Location and setup: Bangalore, India. Datadog states it values office culture and operates as a hybrid workplace, so ask what that means in days per week for this team. Honest fit guidance: this is on the board because a reader asked for Technical Account Manager roles specifically, and it is worth saying that the "Manager" in the title refers to managing accounts, not people. The technical requirements are real, so this suits an engineer or IT operations specialist who wants customer facing work rather than a career account manager. Datadog notes that not everyone will meet every qualification on day one and encourages applying anyway. Its Customer Success Manager Key Accounts role is also on today's board and is the commercial counterpart to this one.
Added July 21, 2026
What the posting requires - 8+ years in systems or infrastructure software engineering, with a meaningful portion on Kafka or comparable distributed systems such as Pulsar, BookKeeper, ZooKeeper, etcd or CockroachDB - Deep familiarity with the Kafka codebase. The posting draws a sharp line here: it wants people who have read, modified and debugged the broker, controller or client internals, not people who have operated Kafka - A track record of upstream contribution: committed patches, participation in KIP discussions, reviewed pull requests or equivalent engagement with the Apache Kafka community. Committer or PMC status is strongly preferred but not strictly required - Strong distributed systems fundamentals understood as engineering tradeoffs you have navigated: consensus protocols, replication, exactly once semantics, log structured storage and distributed state machines - Systems level programming comfort: JVM internals including garbage collection tuning, memory layout and JIT behaviour; operating system I/O including page cache, fsync semantics and zero copy; and networking including TCP tuning and socket buffers - Experience maintaining a fork or distribution, and managing the tension between carrying local patches and staying mergeable with upstream Counts as a bonus, not a requirement - Apache Kafka committer or PMC membership - Experience with KRaft, the ZooKeeper free controller - Having authored or co-authored a KIP - Kafka Streams or Kafka Connect internals, rather than just usage - Familiarity with Kafka's own test infrastructure including system tests, Trogdor and ducktape What you would actually be doing - Owning the internal Kafka distribution: branches, patch curation, releases and upgrade planning - Contributing upstream to Apache Kafka - Diagnosing and fixing deep broker and controller issues across replication, partition reassignment, KRaft consensus, log storage and protocol handling - Building custom patches for production needs unsuited to upstream - Establishing how the team tests, benchmarks and validates patches before rollout - Mentoring a supporting engineer and growing the team's capability - Advising platform teams on configuration, capacity planning and architecture, and acting as the primary interface for audit and compliance Location and working pattern Bangalore. Staff at PhonePe is a senior individual contributor track. Also worth knowing PhonePe's listed benefits include comprehensive insurance, an onsite medical centre, parental and adoption support, relocation help, provident fund and gratuity, higher education assistance and a car lease policy. A good fit if You have gone deep on infrastructure internals rather than broad across product features, and you want one of the few Indian roles that will pay you to work on an open source distributed system at source level. Think twice if You have operated Kafka but never modified it. The posting makes that distinction explicitly, and the interview will go straight there.
What the posting requires - 3 to 6 years building and operating production backend systems at scale - Expert level in at least one modern backend language such as Python, Ruby, Go, Java or Node.js, with strong fundamentals across the stack - Proven ability to design distributed systems, having made real architectural decisions on service decomposition, data consistency, fault tolerance and observability - Deep expertise with relational databases such as PostgreSQL and MySQL plus NoSQL stores, including schema design, query optimisation and modelling for high throughput - Strong understanding of caching with Redis or Memcached, asynchronous messaging with Kafka or RabbitMQ, and event driven architecture - Hands on containerisation with Docker and Kubernetes, CI/CD pipelines and infrastructure as code - A track record of taking technical projects from an ambiguous problem statement through to production Read the AI section before you apply Unusually, HackerRank lists AI fluency as its own requirement block rather than a bonus, and asks for: - Deep hands on proficiency with AI powered development tools such as GitHub Copilot, Cursor or Claude Code, to the point where you have built workflows and practices you could teach to others - Strong working knowledge of large language models and agentic systems, including capabilities, limitations, context management and tool use - Proven ability to use AI across the full development lifecycle: architecture exploration, implementation, code review, test generation, documentation, incident analysis and technical writing - Solid understanding of AI and ML fundamentals: transformer architectures, embedding models, inference optimisation, retrieval augmented generation, the tradeoff between fine tuning and prompt engineering, and evaluation methods - The ability to evaluate AI tooling and integration patterns on cost, latency, reliability and security Counts as a bonus, not a requirement - Systems serving millions of concurrent users under strict latency and availability requirements - Deep expertise in patterns such as microservices, CQRS, event sourcing or domain driven design - Significant cloud experience across AWS, GCP or Azure including serverless and cost optimisation - Building platform level APIs, SDKs or developer tools used by other engineering teams - A history of improving engineering culture, through RFC processes, architecture review boards or engineering blog writing Location and working pattern Hybrid in Bangalore, so plan for regular office days. A good fit if You have a few years of backend work and want a product where reliability genuinely matters, and you are already comfortable working with AI tooling rather than avoiding it. Think twice if You have kept AI tools at arm's length. That section is long, specific and clearly being screened on, and it is the part of this posting most likely to decide the outcome.
What the posting requires - 4+ years building and shipping machine learning systems that run in production at scale - Proficiency in Python, with practical experience building data pipelines and deploying models - Systems thinking, which the posting defines precisely: model accuracy, data pipelines, serving infrastructure and customer outcomes are one problem, not four - Treating evaluation methodology as seriously as model performance, on the stated view that a metric measured wrong is worse than no metric Counts as a bonus, not a requirement - Multimodal systems across vision, natural language, audio or behavioural signal pipelines - Large language model experience including fine tuning, RLHF or multi turn agentic systems - A background in adversarial machine learning, fraud detection or anomaly detection - Publications or open source contributions in detection, robustness or evaluation methodology What you would actually be doing - Designing and shipping production machine learning across the Chakra, integrity and evaluation domains - Owning the full lifecycle: problem framing, data strategy, experimentation, deployment and iteration - Building evaluation infrastructure and benchmarking pipelines that measure model quality reliably before and after deployment - Defining the architecture and production bar for new signal categories from scratch - Mentoring junior machine learning engineers and establishing team practice for monitoring, feedback loops and quality standards Location and working pattern Hybrid in Bangalore. The company is explicit about who thrives here The posting says you will do well if messy, undefined problems interest you more than optimising inside clean ones, if ambiguity energises you when the right framing is itself part of the work, and if defining what a system should be appeals more than maintaining what already exists. It also offers direct access to leadership and fast feedback loops. A good fit if You have production machine learning experience and want genuinely unsolved problems. Detecting AI assisted cheating and redefining how coding skill is measured are live, open questions, and few Indian roles work on them directly. Think twice if You want a stable, well specified roadmap, or your machine learning work has been mostly research without deployment. The requirement is specifically shipping systems that run in production at scale.
What the posting requires - Over 8 years building and operating production grade services with clear ownership of outcomes - Strong system design and distributed systems, hands on across AWS or GCP, containers and Kubernetes, infrastructure as code with Terraform, and CI/CD automation - Depth in one or more of Go, Java, Ruby, Python or JavaScript, plus the ability to pick up new languages and frameworks quickly - Proficiency with PostgreSQL or MySQL and NoSQL databases, and experience with event driven architectures using Kafka or similar for streaming and async work - Excellent communication: writing clear documentation, explaining tradeoffs simply, mentoring peers and influencing across teams without direct authority Counts as a bonus, not a requirement - Exposure to AI systems in production such as language model gateways, prompt or model evaluation, and guardrails - Experience improving developer experience across a company - Public artefacts such as design write ups, talks or open source contributions What you would actually be doing - Aligning the engineering roadmap with business outcomes, and communicating the tradeoffs in plain language - Designing and evolving core API, data and AI platforms that stay scalable, observable, secure and cost aware under thousands of concurrent sessions and bursty traffic - Embedding AI as a first class concern: request orchestration, evaluation harnesses, guardrails and safety, and prompt and data governance - Partnering with product managers and customer facing teams to drive impact - Mentoring through reviews, design reviews and hands on pairing Location and working pattern Hybrid in Bangalore. A good fit if You have most of a decade of backend experience and want platform ownership at a product engineers choose to use, and you are as comfortable writing a design document as writing code. The posting says outright that it values balancing long term decisions with fast incremental delivery, and caring about developer experience as much as raw performance. Think twice if You want a pure coding role. A large share of this one is judgement, communication, roadmap and influence, and the posting weights communication unusually heavily for an engineering listing.
What the posting requires - 3 to 5 years as a database developer or engineer, with exposure to migration work - Working experience with at least one of Oracle, Microsoft SQL Server, or PostgreSQL and Aurora PostgreSQL - A bachelor's degree in computer science or a related field What you would actually be doing - Converting SQL, stored procedures and database objects into PostgreSQL compatible SQL and PL/pgSQL, escalating complex or ambiguous cases to a senior engineer - Working through AWS Schema Conversion Tool findings and flagging limitations that need senior review - Maintaining the Flyway migration codebase: versioned scripts, repeatable migrations and rollbacks - Identifying and troubleshooting database related application bugs, with support on the harder ones - Supporting PostgreSQL query optimisation through execution plans, indexing and query rewrites - Monitoring AWS DMS during full load and change data capture phases, and helping diagnose data and performance issues - Validating and reconciling data between source and target databases, which the posting describes as proof rather than confidence - Working with application teams to align SQL behaviour and performance expectations before cutover Location and working pattern Mumbai. This is consulting delivery, so the work is organised around client engagements and committed cutover dates. A good fit if You are a database engineer who wants AWS depth, or a backend engineer who has drifted into data work and wants to make that the specialism. The escalation path is unusually clearly described, which makes it a reasonable step up rather than a role that quietly expects senior judgement. Think twice if You want product engineering. This is client facing modernisation work with the deadlines and delivery pressure that implies, and much of the day is careful, detailed conversion and verification rather than green field building.
What the posting requires Core Python and systems - Strong Python with 4+ years in production: asyncio, performance optimisation and idiomatic code - A solid grasp of distributed systems concepts: state machines, retries, idempotency and eventual consistency - Integrating language model APIs from Anthropic, OpenAI or similar in production code, covering streaming, function calling, structured output, retries and prompt management - Comfort with FastAPI or an equivalent async web framework Cloud and infrastructure - Working knowledge of AWS: EKS, ECS Fargate, S3, DynamoDB, Lambda, Secrets Manager and CloudWatch - Docker and Kubernetes, including writing Dockerfiles, Helm charts and manifests - CI/CD pipelines, with GitHub Actions preferred - Comfort navigating multi account AWS environments across dev, UAT and production Testing and automation - Test driven development as a discipline, with tests written before the code - Hands on pytest, integration testing and end to end testing - The ability to design behaviour verification harnesses: dual run, output comparison and equivalence proof - Using AI tools such as Claude, Copilot or LLM based test generators to improve test quality Explicitly not required The posting states that you do not need prior Amazon Bedrock or LangChain experience. What it wants is a strong Python engineer who will learn agent frameworks properly. That makes this genuinely open to backend engineers who have not worked on agents before, which is unusual for this kind of role. What you would actually be doing - Building and shipping specialised agents: parsers, business rule extractors, dependency mappers, test synthesizers, behaviour replayers and the orchestration between them - Designing agents that operate against a code intelligence graph so every action traces to a line of code - Implementing governed autonomy through shadow, supervised and autonomous stages with human review at each - Orchestrating frontier models from Anthropic, OpenAI and Google, choosing the right model per task - Owning delivery of your agents from prototype through deployment and post release validation The interview process, as published Mactores lists its process openly, which is rare and worth preparing for specifically. There is a hands on technical session with a panel member covering your skills, experience and how you deliver quality under pressure, then a structured panel interview covering experience, product thinking and how you work, then a 30 minute HR discussion about the offer and next steps. The posting also asks applicants to answer as many of the application questions as possible to speed things up. Location and working pattern Mumbai. A good fit if You are a strong Python engineer curious about agent systems but have been put off by postings that demand specific framework experience. Think twice if You dislike heavy test discipline. Testing runs through this entire posting, including test driven development as a stated requirement and the ability to build equivalence proof harnesses.
What the posting requires - A B.E., B.Tech, M.E., M.Tech or PhD in computer science or equivalent - 6+ years with computer science fundamentals and experience with at least one of Go, Java or Python - Proficiency using AI coding tools such as Claude Code, Codex or Cursor across the full software development lifecycle, covering design, code generation, testing, monitoring and release. DoorDash lists this as a requirement rather than a bonus - Prior technical experience in big data infrastructure and in cost efficiency and governance, having built meaningful pieces of data infrastructure - Experience improving the efficiency, scalability and stability of data platforms - Experience building or operating backend systems in production Counts as a bonus, not a requirement - Having built data infrastructure on open sourced technologies such as Spark or ClickHouse What you would actually be doing - Working across data infrastructure, reliability, governance, developer tooling and AI systems - Supporting thousands of internal data users including engineers, analysts, data scientists and business stakeholders - Helping establish a founding engineering team in India, with the ownership and direct influence that implies Location and working pattern Pune. A good fit if You have solid backend or data platform experience and want early team influence rather than a defined slot in an existing structure. Note also that the AI tooling requirement is stated plainly, so make sure you can speak to how you actually use these tools day to day rather than in the abstract. Think twice if You want a settled team, established process and a clear roadmap. Founding teams trade that stability for ownership, and the posting is honest that this is one.
What the posting requires - 8+ years of professional experience as a hands on engineer and technical leader, leading multiple projects - 6+ years working specifically in data platform and data engineering or a similar role - Proficiency in Python, Kotlin or Scala - 4+ years with ETL orchestration and workflow management tools such as Airflow - 4+ years with the distributed data ecosystem such as Spark and Presto, and streaming technologies such as Kafka, Flink or Spark Streaming - Expert level database fundamentals, SQL, data reliability practices and distributed computing - Proficiency using AI coding tools such as Claude Code, Codex or Cursor across the full development lifecycle, which DoorDash asks for explicitly - Excellent communication with both technical and non technical teams, and knowledge of reporting tools What you would actually be doing - Acting as technical lead, architecting and scaling data reliability, infrastructure, automation and tooling - Owning critical data systems that support multiple products and teams - Developing, implementing and enforcing best practices for data infrastructure - Improving the reliability and scalability of ingestion, data processing, ETL, reporting tools and data ecosystem services Location and working pattern Hyderabad. A good fit if You have led data platform work before and want ownership of systems the business genuinely depends on, including financial reporting where correctness is not negotiable. Think twice if You are still early in a data engineering career, or your data work has been alongside another specialism rather than the main thing. The stacked requirements, 8 years overall and 6 in data, mean a generalist backend engineer with some pipeline experience is unlikely to clear the bar.
What the posting requires - 3+ years of hands on experience in applied machine learning - A strong background in machine learning, deep learning and natural language processing, with proven experience training and fine tuning large scale models such as language models, transformers and diffusion models - Hands on expertise with parameter efficient fine tuning approaches: LoRA, prefix tuning, adapters and quantization aware training - Proficiency in PyTorch, TensorFlow and the Hugging Face ecosystem - Basic understanding of MLOps: experiment tracking, model versioning, CI/CD for ML pipelines and production deployment - Experience with large datasets, feature engineering and data pipelines using tools such as Spark, Databricks or cloud native ML services including SageMaker, Vertex AI or Azure - Knowledge of GPU and TPU optimisation, mixed precision training, and scaling workloads on cloud or HPC environments - Excellent communication, able to explain complex ML concepts to technical and non technical audiences Marked mandatory in the posting - Demonstrated success adapting foundation models to domain specific applications through fine tuning or transfer learning - Strong ability to design, evaluate and improve models using robust validation strategies, bias and fairness checks, and performance optimisation Counts as a bonus, not a requirement - Distributed training frameworks such as DeepSpeed, PyTorch Lightning or Ray - Applied AI work across natural language, computer vision or multimodal systems - Proven ability to lead and mentor junior applied scientists and ML engineers Location and working pattern Bengaluru. A good fit if You have a few years of real modelling work and want problems where the business outcome is measurable, since commerce data gives fast, unambiguous feedback on whether a model is helping. Think twice if Your fine tuning experience is thin. The posting marks foundation model adaptation as mandatory rather than preferred, so it is likely to be a hard filter rather than something you can compensate for elsewhere.
What the posting requires - 3 to 6 years designing and developing complex systems - Strong Java, with exceptional software system design, problem solving and object oriented coding skills - Experience with distributed transaction processing systems or asynchronous messaging technology, which the posting states is required rather than preferred - A good understanding of system performance tradeoffs, load balancing and engineering for high availability - A genuine focus on software quality and end to end ownership of the features you build - A BS or MS in computer science, engineering, mathematics, statistics or a similar field Counts as a bonus, not a requirement - Understanding of enterprise information systems, service oriented architectures and operational data stores Read the level carefully The title says Software Development Engineer II, which at many companies signals an early career or new graduate role. The stated requirement starts at three years, so this is squarely mid level. It is one of the clearest examples in today's edition of why the years matter more than the level in the title, and applying to it as a recent graduate would waste your time. Location and working pattern Bengaluru. A good fit if You are a Java backend engineer with a few years behind you who wants data heavy commerce systems and clear ownership of what you build. Think twice if You are a recent graduate, or your Java experience is mostly CRUD web services. The distributed transaction and async messaging requirement is where this posting will actually be decided.
What the posting requires - 4 to 8 years building scalable, highly critical distributed systems - Strong object oriented design skills, the ability to apply design patterns, and what the posting calls an uncanny ability to design intuitive modules and class level interfaces - Strong technical aptitude and good computer science fundamentals - A B.Tech in computer science or equivalent What you would actually be doing - Working on highly maintainable and efficient components and systems - Excelling as an individual contributor, which the posting names as part of the role rather than a consequence of it - Identifying and resolving performance and scalability issues in an increasingly complex enterprise product - Improving the overall quality of the code structure and the product - Designing features alongside architects - Owning scoping, breakdown and implementation independently - Maintaining documentation for the component you work on The scale behind it More than 300 billion events a month, 2,000 plus customers across 40 plus countries. At that volume the interesting problems are throughput, correctness and failure behaviour rather than feature breadth. Location and working pattern Bangalore. A good fit if You have solid backend experience, want data infrastructure at genuinely high event volumes, and specifically want a senior individual contributor track rather than a step toward managing people. Think twice if You are looking for people management or team lead responsibility. The posting deliberately points the other way, and independence is a stated expectation rather than something you grow into.
What the posting requires - 8+ years of experience in software development, from an enterprise background - Experience with popular open source data processing engines such as Spark, Kafka or Flink, or equivalent - Experience developing with concurrent and non blocking systems - A bachelor's degree in computer science, software engineering or a related field, or equivalent experience The broader stack spans Java, Python, Go and C++. What you would actually be doing Engineering on the core pipeline engine behind a platform handling more than 300 billion events a month for over 2,000 customers across 40 plus countries. The problems at that scale are throughput, backpressure, correctness under load and failure behaviour rather than feature breadth. Location and working pattern Bangalore. A good fit if You have deep backend systems experience and want data infrastructure at scale. If you have specifically worked on concurrency and non blocking systems, this posting is asking for you more directly than most listings do, and that is worth leading with in your application. Think twice if Your experience is mainly request and response web services or CRUD applications. The concurrency requirement is called out separately from the general experience bar, which usually means it is a real filter rather than a preference.
What the posting requires - 6+ years of backend engineering building distributed systems, platform services or large scale backend applications - Strong proficiency in one or more common backend languages such as JavaScript, Python, Java, Go, PHP or C++ - Experience designing APIs, frameworks or platform abstractions used by multiple engineering teams - A strong understanding of reliability, observability, operational excellence and system failure modes - Experience with event driven architectures, messaging systems, queues, workflow engines or orchestration platforms - The ability to translate product requirements into durable, scalable platform capabilities - A collaborative mindset, with experience driving alignment across teams that have different priorities - A preference for simple, reliable solutions over unnecessary complexity - Strong communication and the ownership to move ambiguous projects from idea to production Counts as a bonus, not a requirement - Curiosity about AI and agentic product experiences, and how infrastructure needs to evolve to support them Know this before you apply Postman is direct about its in office model. Staff at its hubs in the San Francisco Bay Area, Boston, Austin, New York, Tokyo and London are in office five days a week. For roles based in Bangalore, employees currently work in the office three days a week and will transition to five days per week by the end of the year. If you are optimising for hybrid or remote flexibility, factor that in now rather than at offer stage. Location and working pattern Bengaluru, on the schedule described above. A good fit if You have genuine distributed systems depth, want to build platform capabilities other engineers depend on, and are happy working in an office. Think twice if Remote or hybrid flexibility matters to you. The direction of travel here is explicitly toward five days a week in office, and the posting states it rather than leaving it to be discovered.
What the posting requires - 10+ years of hands on coding, with familiarity across common programming languages such as C, C++, Java, PHP, Python, JavaScript and NodeJS - 10+ years of engineering experience building end to end backend services - Strong experience with security offerings such as vault stores, token scanning and cryptography - Demonstrated experience leading cross functional projects with meaningful impact on the business - Exceptional problem solving, design and analytical skills - Demonstrated experience designing highly scalable systems - A bachelor's degree in a computer science related field, or equivalent practical experience What the work concentrates on Keeping the platform trustworthy for a user base that stores credentials and secrets alongside their API work. The named security areas, vault storage, token scanning and cryptography, point at secret handling and leak prevention rather than general application security. Know this before you apply The same in office model applies as Postman's other Bengaluru opening: employees based in Bangalore currently work in the office three days a week, moving to five days per week by the end of the year. Location and working pattern Bengaluru, on the schedule above. A good fit if You have a decade of backend engineering and want scope over trust, security and reliability rather than feature delivery, and you have real cryptography or secret management experience to point to. Think twice if You are earlier in your career, or your security exposure is general rather than hands on with vaults, tokens and cryptography. Both the coding and the backend service requirements are stated as ten years, so this is not a stretch application.
What the posting requires - A degree in computer science - 3 to 5 years of experience with C and C++ and object oriented programming - Expertise in algorithms and data structures - A working knowledge of Linux systems - Excellent problem solving skills and strong communication - Experience in the high frequency trading industry is listed among the requirements Also mentioned in the posting - Familiarity with other languages including Java, Scala, Python, bash and Lisp - Familiarity with parallel programming models and parallel algorithms - Experience with big data environments What you would actually be doing - Designing and implementing a high frequency automated trading system that trades on multiple exchanges - Building live reporting and administration tools for that trading system - Performance optimisation and improving overall system latency through algorithm research and current technology Location and working pattern Gurugram. How to prepare Quantitative trading firms interview hard on data structures, algorithms, systems internals and low level performance, and Graviton describes its team in those terms. If you are applying, prepare for that specifically rather than for a general backend interview. Domain knowledge of finance is usually not required, and these firms hire primarily on engineering ability, so a strong systems background without trading experience is still worth an application even though HFT experience appears in the list. A good fit if You write performance sensitive C++, enjoy profiling and optimisation, and want work where microseconds are measured and genuinely matter commercially. Think twice if You prefer product breadth or working across a varied stack. This is deep, narrow, latency focused systems engineering, and most of the value you add comes from going further down rather than wider.
What the posting requires - 2 to 5 years of software development experience - 2+ years of product development experience - A BS, MS or PhD in computer science or a related field - Proficiency in one of C++, Java, Go, Scala or Python - The ability to identify scalable and elegant solutions to complex problems - A strong interest in and ability to learn new technologies Counts as a bonus, not a requirement - Full stack development experience What you would actually be doing - Working on the hypervisor protection layer, the most widely protected workload on Rubrik's platform - Building large scale distributed systems that serve both cloud and on premise protection - Designing, developing, testing, deploying, maintaining and improving the products, drawing on your experience with large software systems - Driving large projects end to end, working independently or partnering closely with other engineers Location and working pattern Bangalore. Why this one is worth a look if you are earlier in your career At 2 to 5 years it is the most accessible role in today's edition, and it asks for only one language from a fairly broad list rather than deep expertise across a stack. Distributed systems and storage is also a specialisation that holds its value for a long time, so it is a useful direction to move in early. The posting explicitly values willingness to learn new technologies, which suggests the team expects to bring people up rather than hire fully formed specialists. One practical note Rubrik's application page sits behind bot protection and can be slow to load or refuse automated traffic. We confirmed this posting is live and open. If the link does not open first time, try again in a normal browser window. Think twice if You want to specialise in application or product feature work. This is systems and infrastructure engineering at the storage and virtualisation layer.
What the posting requires - 9+ years of software engineering with a deep backend and infrastructure focus - Strong Python and/or Go. The posting is pointed here, asking for people who ship production code rather than scripts and configuration - Deep hands on Kubernetes: building and operating clusters, not just deploying onto them - Proven experience designing and operating distributed systems in production - Cloud native fluency across AWS and/or GCP spanning compute, storage, identity and access management, networking and managed services - Experience with infrastructure as code using Terraform or similar, and CI/CD pipelines - Familiarity with applied AI tooling and patterns, including agentic AI tools, AI gateways and agent frameworks, and the ability to build backend services that integrate with them - Strong system design and architectural judgement - Clear communication, partnering across product, security and AI teams Counts as a bonus, not a requirement - Observability stacks such as Prometheus, Grafana, Datadog or OpenTelemetry - Multi cloud or hybrid infrastructure experience across AWS, GCP and on premise Read where this role sits Rubrik places this position in its Information Technology organisation rather than core product engineering. That team centralises infrastructure, technology and data management to create operational efficiency as the company scales, and owns the secure environment the development lifecycle runs in. The AI capability you would build is for internal use. Location and working pattern Bangalore. One practical note Rubrik's application page sits behind bot protection and may refuse automated traffic or load slowly. We confirmed this posting is live. If it does not open first time, retry in a normal browser window. A good fit if You are experienced, genuinely interested in enterprise AI and internal platform engineering, and you want deep infrastructure work with modern AI tooling attached. Think twice if You specifically want to build a product customers buy. Rubrik's hypervisor opening in this same edition is the product engineering one, and the two lead to quite different careers.
What the posting requires - 3+ years with Apex, Lightning Web Components, SOQL and JavaScript, working in an Agile team - Force.com coding standards and the Salesforce Lightning Design System - Experience spotting the blind spots and bugs specific to Salesforce - Experience working with and optimising millions of rows of data - CSS, HTML and jQuery - Version control with Git or SVN - Writing unit tests with assertions for core functionality - The ability to turn technical requirements into independent features, with real debugging depth Counts as a bonus, not a requirement - AgentForce, Einstein and other AI tooling - SQL, Python, Data Cloud and Snowflake - Familiarity with a pay as you go business model - Building and deploying through Heroku - Conga or Apttus CPQ or CLM What you would actually be doing - Evolving the Salesforce data model behind Twilio's sales systems so it stays scalable and intuitive for the people using it - Building custom functionality using SOQL APIs, Apex controllers, Apex web services and Apex callouts - Running technical analysis, documenting integration requirements, and working with architects on integration design - Reviewing code quality across the codebase and refactoring for extensibility Location and working pattern Remote, but not from anywhere in India. The posting names five states: Karnataka, Tamil Nadu, Telangana, Maharashtra and New Delhi. Check you are in one before applying. Occasional travel may be required for project or team meetings in person. Also worth knowing Twilio lists competitive pay, generous time off, parental and wellness leave, healthcare and a retirement savings programme, noting that offerings vary by location. Twilio also states that it uses AI to make its hiring process more efficient, while every hiring decision is made by a person. A good fit if You are already a Salesforce developer with around three years behind you, and you want that skill inside a large global product company on a remote Indian contract. Think twice if You are a general backend or full stack engineer. Very little transfers here without Salesforce platform experience, and the required list is specific about it. The other two Twilio roles in today's edition are ordinary software engineering.
What the posting requires - 7+ years of applied machine learning with strong Python - A real grounding in machine learning foundations and the building blocks of modern deep learning - A track record of building, shipping and maintaining models in production in an ambiguous, fast paced environment - Experience designing large scale experiments and analysis that inform a product roadmap - Understanding of why frameworks like PyTorch, TensorFlow or Keras work as they do, not just how to call them - MLOps familiarity: testing, retraining and monitoring models once live - The ability to ramp up quickly in unfamiliar business domains - Exposure to modern data storage, messaging and processing tools such as Kafka, Spark, Hadoop, Presto and DynamoDB, including coding against big data components - Experience working in an agile team with shifting priorities - Experience working on AWS Counts as a bonus, not a requirement - Experience with large language models What you would actually be doing - Building and maintaining scalable machine learning in production - Training and validating deep learning and statistical models, weighing use case, complexity, performance and robustness - Developing an end to end understanding of the systems and the reasoning behind them - Partnering with product managers, tech leads and stakeholders to scope what needs building - Working with data platform teams on robust batch and real time pipelines - Mentoring, knowledge sharing, and upholding code review, automated testing and monitoring practice Location and working pattern Remote and based in India. Unlike Twilio's other two openings today, this one states no restriction to particular states. Occasional travel may be required for in person team meetings. Also worth knowing Twilio lists competitive pay, generous time off, parental and wellness leave, healthcare and a retirement savings programme, varying by location. A good fit if You have several years of production machine learning and want unusual scale plus a genuinely remote Indian role. Think twice if Your experience is mostly notebooks, coursework or research without deployment. The posting returns repeatedly to shipping and maintaining models, not building them once.
What the posting requires - 12+ years designing and building highly available, high scale, secure, mission critical cloud SaaS applications in Java, Go or Python - Knowledge of architectural patterns for mature services, especially distributed and multi regional deployments - Strong high level service design: modelling interfaces and internals so they stay modular, composable and extensible - AWS, GCP or another public cloud, with multi region deployment a plus - Building distributed systems at scale on a microservices architecture - Extensive REST API design and implementation - Data architecture experience such as ClickHouse, Lakehouse or Snowflake - SQL and NoSQL databases and caches - Familiarity with streaming systems such as Kafka, Flink or Spark - Container technologies, Docker and Kubernetes - Modern automated testing and CI/CD pipelines, with genuine ownership of develop, test and deploy - Strong track record solving complex production issues What you would actually be doing - Leading architecture and system design for complex distributed systems, and guiding teams toward maintainable solutions - Writing and reviewing high quality code for core services, APIs and platforms - Turning business goals into technical roadmaps and aligning stakeholders on direction - Improving resiliency, latency, throughput and cost efficiency, and establishing SLOs, SLAs and operational practice - Driving standards for coding, testing, CI/CD, observability, security and documentation - Coaching and mentoring engineers at every level, leading design reviews, postmortems and technical deep dives - Identifying security, scalability and compliance risks early and driving mitigation Location and working pattern Remote, but restricted to five Indian states: Karnataka, Tamil Nadu, Telangana, Maharashtra and New Delhi. Occasional travel may be required for in person meetings. A good fit if You are an experienced architect who wants breadth across many teams while staying hands on, working remotely from India. Think twice if You are below roughly a decade of experience. If you are earlier in your career, the requirement list is still worth reading as a map of what deep distributed systems specialisation builds toward.
What the posting requires - 3 to 5 years as a machine learning engineer, with a track record of building and deploying ML systems - Hands on experience creating generative AI systems including large language models and retrieval augmented generation, plus a clear history of operationalising agentic AI in production - Deep understanding of MLOps and LLMOps, specifically the monitoring, observability and debugging problems created by non deterministic agents - A solid computer science foundation in data structures and algorithms - Python expertise with scikit-learn and PyTorch or TensorFlow, plus SQL for feature engineering and model evaluation - Strong communication, able to work independently and in a team Counts as a bonus, not a requirement - Cloud services such as AWS, GCP or Azure, and ML platforms such as Kubeflow or SageMaker - Familiarity with systems programming or distributed systems - Visible contribution to the field such as technical blogs, papers or industry knowledge sharing What you would actually be doing - Independently developing machine learning models and generative AI solutions, with the emphasis on building and deploying agentic architectures - Driving AI agents end to end into production, handling multi step reasoning, tool use, state management and model orchestration in live environments - Designing LLMOps frameworks that give real observability, monitoring, logging and evaluation for agents - Refining and optimising both generative pipelines and existing classical models through feature engineering and hyperparameter tuning - Working with cross functional teams to turn business needs into technical solutions Location and working pattern A hybrid position based in Bangalore, reporting to the Manager of Machine Learning Engineering. A good fit if You have shipped machine learning before and want to move into agent based systems, on a security product where a mistake has real consequences. Security data is adversarial in a way most recommendation and forecasting work is not, because someone is actively trying to defeat your model. Think twice if You have only used language models through an API. The posting asks specifically for agents you have run in production, and repeats the point about non deterministic behaviour, which is where that experience shows.
What the posting requires - 4+ years in automation testing, preferably within an enterprise or cloud environment - A foundational understanding of AI and machine learning, and experience using AI driven approaches in your own domain, which Zscaler asks for across its engineering roles - The Python, Kubernetes and networking combination named in the title, all three of which the role genuinely depends on What you would actually be doing - Designing scalable, reusable and maintainable test automation frameworks using an AI first development approach - Writing and running end to end tests across ZDX components: cloud services, analytics dashboards, APIs and user facing applications - Working with engineering and DevOps to integrate testing pipelines into CI/CD so release cycles stay fast without losing quality - Using analytics tools, logs and test output to find bottlenecks and troubleshoot systematically - Continuously refining test methodology to improve coverage and catch issues earlier Location and working pattern Bangalore, in the Platform and Reliability Engineering department, reporting to the Director of Platform and Reliability Engineering. Zscaler operates a hybrid working model. A good fit if Your background is QA automation or SDET work and you want to go deeper into Kubernetes and networking. That combination is what makes this more valuable long term than generic test automation, and it is a realistic route out of pure manual or scripted QA. Think twice if You want to build product features. This is a testing, tooling and reliability role. Also do not treat the networking requirement as decoration: it is in the title, and ZDX is a network and digital experience product, so expect it in the interview.
What the posting requires - 5+ years as a software engineer or machine learning engineer - Experience applying machine learning to improve key business metrics, optimising models for both accuracy and latency - Experience researching newer techniques and innovating to build ML based solutions - Experience with the algorithms behind data collection and processing infrastructure, model training, and serving platforms - Deep expertise with AWS Counts as a bonus, not a requirement - A proven track record designing, building and shipping end to end applications at scale - Experience identifying and solving problems in data using machine learning systems - Familiarity with multi agent systems, agent architectures, prompt engineering and current AI frameworks What you would actually be doing - Building and maintaining large scale distributed systems covering the whole pipeline: data collection, feature engineering, model training, evaluation, deployment and real time serving - Writing functional specifications, assessing task requirements and scheduling, and staying involved through development, debugging and support - Solving problems such as threat detection and business intelligence in direct collaboration with data scientists, product management and product engineering Location and working pattern Based in Bangalore, reporting to the Manager of Machine Learning Engineering. Zscaler operates a hybrid working model. A good fit if You have several years of production machine learning and want an adversarial domain. Threat detection behaves very differently from the recommendation and forecasting problems most machine learning engineers see, because the data changes in response to your model. Think twice if You prefer modelling to infrastructure. A large part of this role is the distributed systems underneath the models, and the posting leads with that rather than with modelling technique.
What the posting requires - 13+ years in software development, with at least 8 of those specialising in production grade microservices - Hands on experience in a modern language such as Java, Go or Rust - Expertise in distributed data patterns including CQRS and event sourcing, and event driven communication using Kafka, RabbitMQ or SQS - Extensive hands on Docker and Kubernetes within AWS, Azure or GCP - Proficiency in both SQL (PostgreSQL, MySQL) and NoSQL (Cassandra, MongoDB or Cosmos DB) design and scaling - A foundational understanding of AI and machine learning, and experience applying it in your own domain Counts as a bonus, not a requirement - Implementing AI assisted engineering tools, or integrating predictive models to improve control plane resiliency and automated scaling - Service mesh technologies such as Istio or Linkerd - Practical chaos engineering and advanced performance testing What you would actually be doing - Leading the technical roadmap to modernise enterprise platforms using API first design and microservices - Designing and deploying highly resilient, low latency, event driven solutions, owning them from the API tier through to back end services - Setting coding standards, performing code reviews, and championing test driven and behaviour driven development - Partnering with product, DevOps and system architects to turn business needs into scalable technical solutions - Managing service lifecycles through Docker and Kubernetes, and monitoring health with tools such as Prometheus and Grafana Location and working pattern A hybrid role based in Bangalore, reporting into senior engineering leadership. A good fit if You have well over a decade of backend depth and want architectural ownership across a platform while staying hands on with code. Think twice if You are early or mid career. This is genuinely a 13 year role. If you are starting out, read the requirements as a picture of what deep backend specialisation looks like across a full career rather than as something to apply for now.
What the posting requires - 3 to 6 years in frontend engineering with shipped, production grade products - Deep React proficiency, TypeScript, modern CSS such as Tailwind, and strong component architecture instincts - State management with Zustand, Redux Toolkit or equivalent, plus solid async data patterns - Data visualisation experience with at least one of D3.js, Mapbox or Leaflet, Deck.gl for geospatial, or Recharts, used in production - REST and WebSocket integration, with enough backend awareness to debug across the boundary - Performance engineering: bundle optimisation, lazy loading and rendering performance in low resource environments Counts as a bonus, not a requirement - WebGL or Three.js for 3D visualisation - Electron or desktop application experience - Offline first or progressive web app architecture - Prior work on dashboards, command and control interfaces, or complex enterprise tooling What you would actually be doing - Building production grade interfaces for strategic sector and enterprise AI use cases, including geospatial overlays, simulation interfaces, ontology viewers and data ingestion dashboards - Owning the frontend layer of atoms end to end, from component architecture through deployment into client embedded environments - Building for genuinely constrained conditions: offline first, low bandwidth and limited hardware - Contributing to shared frontend infrastructure, component libraries, the design system and state management patterns - Joining field testing and client feedback loops alongside the deployment engineers Worth knowing before you self reject Sarvam adds a note to this posting saying it is looking for people who can own the outcomes described, not people who match every line of the specification. If the problem interests you and you believe you can do the work, the company is explicitly inviting you to apply. A good fit if You are a frontend engineer who wants to work close to real AI systems rather than on marketing pages, and you find hard constraints interesting rather than irritating. Think twice if You are used to shipping to modern browsers on fast connections and would rather not think about offline behaviour or locked down client machines. That constraint runs through the entire role.
What the posting requires - 3 to 5 years in machine learning engineering or MLOps, with at least one production language model or ML system in continuous operation - Deep model serving expertise using vLLM, TGI, Triton Inference Server or equivalent, including quantised formats such as GGUF, AWQ or GPTQ - Experience fine tuning and adapting models in constrained, on premise or air gapped environments, managing the data pipeline and compute limits those bring - Containerisation with Docker and Kubernetes, or lightweight alternatives such as K3s or K0s for constrained and edge deployments, across varied hardware - Monitoring and observability with Prometheus, Grafana or equivalent, including building custom evaluation dashboards - Python fluency, with familiarity with fine tuning workflows and model evaluation frameworks - CI/CD tooling for ML pipelines such as GitHub Actions, ArgoCD or DVC The signals they say they look for - You have kept a production ML system running under load, and debugged it when it broke - You do not wait for failures, you build systems that warn you before they happen - You write documentation that people other than you actually use What you would actually be doing - Designing and operating model serving infrastructure across on premise and cloud deployments - Building CI/CD pipelines for model updates, rollbacks and evaluation gated releases - Monitoring latency, accuracy drift, throughput and failure modes, and building systems that surface problems before clients notice - Building evaluation infrastructure: harnesses, A/B testing and model comparison tooling for both lab and field use - Managing containerised serving in constrained, air gapped and edge environments - Writing runbooks and operational playbooks for deployment engineers in the field - Owning incident response for model layer failures across every active deployment Location and working pattern Based in Delhi rather than Bengaluru, which is worth noting because most Indian AI roles cluster in Bangalore. A good fit if You would rather keep models running reliably than train them, and you treat uptime and correctness as equally non negotiable. Think twice if You want research or modelling work. This is squarely infrastructure, reliability and operations, and the air gapped and edge constraints mean the usual managed cloud conveniences often are not available.
What the posting requires - 4 to 8 years in data infrastructure, data engineering, platform engineering or site reliability engineering, ideally somewhere operating at significant data scale - Direct experience managing multi terabyte data stores, having personally built or operated systems holding 10TB or more with sustained high throughput ingestion - Deep working knowledge of at least two of PostgreSQL, MongoDB, Elasticsearch, ClickHouse or comparable systems, including tuning, indexing, partitioning and operational management - Production ingestion pipelines built with Kafka, Spark, Airflow, Flink, dbt or equivalent - Strong Python and/or Go, writing production infrastructure tooling and automation - Solid understanding of storage systems and formats: object storage such as S3 or MinIO, columnar formats such as Parquet and ORC, and how to pick the right layer for a workload - Containerisation and orchestration with Docker and Kubernetes in production - Infrastructure as code and deployment automation with Terraform or similar Counts as a bonus, not a requirement - Vector databases or embedding stores such as Milvus, Weaviate, Qdrant or pgvector - Deploying and operating infrastructure in air gapped, on premise or hybrid environments What you would actually be doing - Designing and operating storage architectures across relational, document, vector and object stores at terabyte scale and across multiple data types - Building ingestion pipelines that reliably handle daily influx across both batch and streaming workloads - Making the decisions on indexing strategy, pipeline orchestration and system performance - Owning reliability and performance of the infrastructure layer for your assigned accounts Location and working pattern Delhi based, working closely with teams deployed at client sites. Worth knowing before you self reject As with its other openings, Sarvam notes it wants people who can own the outcomes described rather than people matching every line of the specification. A good fit if You are a data or platform engineer comfortable working at customer sites and making architecture decisions without a managed cloud safety net. Think twice if You want to stay on internal systems with modern tooling. Air gapped and operationally sensitive environments are the norm here, not the exception.
What the posting requires - 5+ years of backend or data platform engineering, with a meaningful part of it designing and operating analytics systems in production - A track record of building zero to one platforms that other engineering teams depend on - ClickHouse in production at scale: sharding, replication, MergeTree variants, materialized views, projection design, query tuning, and the operational side including backups, upgrades and capacity planning - Go for high throughput backend services, with a strong grasp of concurrency, performance and API design across REST and gRPC - Kafka as a primary streaming backbone: partitioning strategy, consumer groups, exactly once and idempotency patterns, and schema registry - Debezium based change data capture, built and operated from transactional databases into analytical stores - Strong systems instincts, reasoning about throughput, latency, cost and failure modes before writing code Counts as a bonus, not a requirement - Spark and Airflow for batch enrichment, backfills and scheduled aggregation - Multi tenant SaaS platforms with row level security, per tenant quotas and tenant aware access control - Building or integrating BI and dashboard tools such as Superset, Metabase or Cube, especially embedded customer facing analytics - Exposure to billing or metering data feeds where correctness is not negotiable What you would actually be building - A high throughput event ingestion API in Go that accepts arbitrary event payloads, validates them, and lands them in ClickHouse with automatic table creation - Change data capture replication from product databases into the analytics store - A tenant aware query API and no code dashboard layer feeding customer analytics, internal reporting and billing Location and working pattern On site in Bengaluru, working with a small team of senior engineers. The posting says this directly, so treat it as an on site role rather than hybrid. A good fit if You want to be the technical owner of a foundational platform rather than a feature contributor on someone else's system, you like writing design docs as much as code, and you think about cost per query as well as latency. Staff here means senior individual contributor, so the scope is architectural. Think twice if You prefer a defined slice of an existing system, or you need hybrid or remote flexibility.
What the posting requires - 4+ years of experience in software development - Proficiency in at least two of Rust, Go and Python - Good networking fundamentals and systems knowledge, with exposure to open source technologies - Strong data structures and algorithms - Experience with or knowledge of operating systems and current technologies Counts as a bonus, not a requirement - Awareness of cloud technologies, Mesos, KVM or QEMU, and NodeJS or React What you would actually be doing - Gathering product requirements and designing solutions with stakeholders across different domains - Developing and maintaining in house cloud architecture components, including procurement, provisioning, patching, migration and retirement of instances - Owning implemented solutions end to end, from inception through deployment, monitoring and regular upkeep - Identifying infrastructure wide and company wide problems and providing scalable solutions - Measuring and increasing compliance of those solutions, and bringing a DevOps mindset to how they are implemented Location and working pattern Bangalore. Also worth knowing PhonePe lists a substantial benefits package for full time staff: medical, critical illness, accidental and life insurance, an employee assistance programme with an onsite medical centre, maternity and paternity benefits with adoption and day care support, relocation and transfer support, provident fund, gratuity and leave encashment, plus higher education assistance, car lease and a salary advance policy. A good fit if You are a backend or infrastructure engineer who wants to write Rust professionally rather than as a side project. Roles that will pay you to work in Rust in India are genuinely uncommon, and that is the strongest reason to look at this one. Think twice if You want consumer product work. This is internal reliability and cloud tooling. The posting also asks for two languages rather than one, so pure Python engineers with no systems language exposure are a weaker match.
What the posting requires - 5 to 9 years of full time iOS app development, with strong fundamentals and end to end exposure - Strong system design and architecture skills specifically for iOS, not general mobile experience - Hands on experience with modern iOS technology: Swift, UIKit and SwiftUI, MVVM or VIPER architecture, Combine, Core Data and dependency injection frameworks - Experience with unit testing and UI testing across full end to end app development - Strong problem solving, plus what the posting describes as curiosity to tinker and explore new paradigms Counts as a bonus, not a requirement - Experience developing SDKs Location and working pattern Pune, which is unusual for PhonePe engineering roles and worth knowing if you are based in Maharashtra. Also worth knowing PhonePe lists medical, critical illness, accidental and life insurance, an employee assistance programme with an onsite medical centre, maternity and paternity benefits including adoption and day care support, relocation and transfer support, provident fund, gratuity and leave encashment, plus higher education assistance, car lease and a salary advance policy. A good fit if You are an experienced iOS engineer who wants consumer scale rather than enterprise app work, and you are interested in the problems that only appear at very large install bases. Think twice if You are earlier in your mobile career. The band starts at five years of full time iOS work specifically, so treat it as a target to grow toward rather than a stretch application. If you are a cross platform developer working mainly in React Native or Flutter, note that the requirements are consistently native.
Added July 20, 2026
No years stated. Data pipeline work: ingestion, processing, indexing.
No years stated. Familiarity with OWASP Top 10 and finding real issues.
No years stated, but Go experience is required.
2 to 5 years backend. Java, Spring Boot, Elasticsearch, MongoDB.
2 to 3 years in firmware, embedded systems or a related field.
No years stated. Fullstack, with support from senior and staff engineers.
Bachelor's or master's in CS. About 2 years in test automation or SDET.
About 2 years in test automation. Strong Java, RestAssured, Selenium.
Open only to B.A, B.Com and BBA graduates. About 1 year in technical support.
About 2 years of integration development across enterprise systems.
Strong Java and OOP. Bachelor's in maths, CS or similar. About 1 year.
Bachelor's or master's in CS. About 1 year in test automation or SDET.
About 1 year building tools or test automation.
Basic Java, Linux and CI/CD. About 1 year of experience.
Any technical degree. No years of experience stated in the posting.
Strong ReactJS and TypeScript. No years of experience stated in the posting.
Added July 18, 2026
About 1 year of experience. Degree in Computer Science, Information Security or related.
About 1 year of experience. Hybrid working from Bangalore.
1 to 3 years. Linux systems and middleware experience.
1 to 3 years. QA for IoT devices. Five days per week in office.
About 1 year of experience in systems or cloud infrastructure.
About 1 year of experience. Interest in reliability engineering and production systems.
About 1 year of Android development experience. Kotlin or Java.
About 1 year of experience. Interest in security automation and DevSecOps.
About 1 year of experience. Comfort with data pipelines and debugging.
About 1 year of experience in information security, privacy or compliance.
About 2 years of experience. Production troubleshooting, automation and observability.
About 2 years of hands on high performance computing experience.
About 2 years of Python experience. Data analysis, automation and visualisation.
2 to 4 years. SQL, data modelling and BI tooling.
About 2 years. Strong statistics and evaluation design.
About 2 years. Comfort working directly with client data and stakeholders.
About 2 years. Building with LLMs, APIs and production systems.
About 2 years. Linux, GPU infrastructure and cluster operations.
2 to 4 years as a data engineer. Cloud warehouses and pipelines.
About 2 years. Comfort analysing logs and test data.
2 to 5 years in operations engineering or production support.
About 3 years of data engineering experience. Pipelines and warehousing.
About 3 years of backend engineering experience.
1 to 3 years in network operations or network engineering. Entry level scripting in Python or Go. Knowledge of VxLAN is an advantage.
1 or more years in a similar technical support role. Comfort debugging customer facing issues.
About 2 years each with Terraform, configuration management and Linux administration.
Entry level backend software engineering role (SDE I) on the CommerceIQ engineering team in Bengaluru. Open to 1 to 3 years of experience.
Early career software engineer joining the Instawork Robotics Labs team in Bengaluru.
SQL, PL/SQL and data modeling. Oracle ERP Cloud Financials (BIP and OTBI reports).