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New today · July 28, 2026
What the posting requires: 2 to 4 years of professional software development experience in backend, distributed systems or platform engineering roles. Proven experience building production grade backend services and APIs in Python or Go. Hands on experience deploying, scaling and troubleshooting containers and Kubernetes, with cloud platform familiarity (they note GCP is a plus). Strong debugging and root cause analysis across distributed components. Solid grounding in system design, performance optimisation and reliability engineering. Zscaler also asks for demonstrated curiosity about AI tools and a history of folding them into your daily workflow, and it states this plainly as a minimum qualification rather than a nice to have, so address it in your application. The day to day: designing, developing and maintaining backend services and APIs; owning the full lifecycle from build through deployment, scaling and production support; running containerised workloads on Kubernetes; monitoring service health, investigating incidents and doing root cause analysis; and working alongside the cloud infrastructure teams on workload deployment and configuration. Location and office reality: Mohali, Punjab. Zscaler's India engineering presence spans Bangalore, Mohali, Hyderabad and Pune, and this req is Mohali only, so treat it as an on site role in Punjab unless recruiting tells you otherwise. Who this is for: an engineer roughly 2 to 4 years in who has already run something in production and wants to go deeper on Kubernetes, cloud native services and security infrastructure. If you have only built features behind someone else's deployment pipeline, the full lifecycle ownership language is the part to prepare for. If you are past about 6 years, the other Zscaler listings on this board will fit you better than this one.
What the posting requires: 2 to 4 years of professional software development experience with meaningful time building production frontend applications in TypeScript or JavaScript. Browser extension development experience for Chrome, Firefox or Safari, including a working understanding of extension APIs, manifest versions (MV2 and MV3), permission models, and the separation between content scripts, background service workers and extension pages. Strong command of core JavaScript (ES6 and later) and TypeScript types, async and await, closures and modules, with a precise mental model of how the language behaves. Experience with React. As with the other Zscaler reqs, active use of AI tooling is listed as a minimum qualification. The day to day: turning product requirements and UI or UX designs into tested browser extension features, from user facing UI down to in browser detection logic; writing security sensitive code that runs on every page load with minimal latency and memory overhead; writing unit and integration tests; debugging across background scripts, content scripts and popups with browser developer tools; and partnering with designers, backend engineers and QA. Location and office reality: Mohali, Punjab. Who this is for: a frontend engineer 2 to 4 years in who wants to stop building dashboards and start working on the browser platform itself. The extension experience is the real gate here. If you have never shipped one, the manifest and permission model questions will be hard to bluff, but a serious side project extension is a legitimate way to answer them.
What the posting requires: four to seven years in cyber security research (the posting spells the numbers out in words rather than digits). Strong proficiency in reverse engineering and debugging with tools such as IDA Pro or x64dbg. Deep understanding of Windows internals, web application security, malware categories, and network protocols across TCP/IP and the OWASP frameworks. Proven experience creating detection signatures with IDS or IPS and YARA. Strong programming in Python, Shell, Perl or Ruby for building automation tooling. Demonstrated curiosity about AI tools is again listed under minimum qualifications. Nice to have: experience designing AI powered automation or prompt engineering workflows to scale threat research and analyse malicious AI agents; certifications in AI, prompt engineering or agentic AI workflows; familiarity with the MCP protocol; and a B.E, M.E, B.Tech or M.Tech in computer science or IT, or advanced cybersecurity certifications. The day to day: static and dynamic malware analysis against emerging threats, C2 frameworks and malicious AI agents; building automation tools, prototypes and detection signatures that ship into Zscaler products; tracking attacker tactics and running reputation analysis on extracted indicators; validating AI and ML model output and feeding that back to engineering; and publishing research. Location and office reality: listed for Bangalore, Hyderabad, Mohali or Pune, and tagged hybrid in the posting itself. Who this is for: a malware analyst or detection engineer with real reverse engineering hours who wants to move toward the AI side of security research without leaving hands on analysis behind. Note the reporting line is into a leader in the Threat Detection Group, and despite the Staff title the years asked for are 4 to 7, which is lower than most Staff titles on this board.
What the posting requires: a bachelor's degree or higher in computer science or engineering, or comparable education and experience, which it defines as typically obtained by five or more years of related work experience. That sentence is the only experience figure in the posting, so treat 5 years as the floor. Beyond that: sound grasp of cybersecurity practice; broad technical knowledge of Windows, Mac and Linux, networking protocols, cloud infrastructure, security devices (firewalls, IPS and IDS, DLP) and SIEM tooling (Splunk, Sumo Logic, Elastic, Kibana); hands on secrets management and PKI including HSMs, certificate generation and re key operations at scale; deep practical virtualisation experience (ESXi, Hyper-V, KVM, Kubernetes, OpenStack); strong networking fundamentals including the OSI model, SDN and cloud VPCs; hands on public cloud (AWS, GCP, Azure); a track record running projects from scoping through documentation; experience across both commercial and public sector environments; and broad Linux administration across varied distributions. The day to day: designing, building and operating security systems; monitoring the security environment and identifying gaps; preparing security reports from collected data and trends; determining security requirements from business strategy and researching standards; running system security and vulnerability analyses and risk assessments; conducting incident response analyses; and mentoring less experienced team members and running training. Location and office reality: Bengaluru. Netskope's India engineering base. Who this is for: an infrastructure or platform security engineer, not a machine learning specialist. If you came for AI model security this is not that job, and the honest read of the requirement list is production infrastructure security with PKI and virtualisation depth. The hiring across all levels note means candidates well past 5 years are also in scope.
What the posting requires: a bachelor's degree in ECE or EEE. 6 or more years of hardware development experience, with the header stating a 6 to 10 year band. Proficiency with OrCAD, Mentor and Cadence. Strong problem solving and debugging. Knowledge of schematic, PCB and Gerber review. Hands on experience with board bring up and field installed system debugging. Hands on qualification experience across ESS, EMI and EMC. Understanding of cellular technologies including GSM, LTE and 5G. Experience with test and measurement equipment including high end oscilloscopes and logic, spectrum and vector network analysers. Nice to have: prior experience at product companies, design experience on Qualcomm or NVIDIA platforms, and experience with camera sensors and AI processors. The day to day: designing and reviewing high speed system hardware; working with the software team on system level issues; supporting manufacturing for production quality; working across mechanical, ECAD, BSP, CE and supply chain teams; and designing for test strategy and sustaining test support across the product lifecycle. Location and office reality: HM Tech Park, Whitefield, Bangalore. Netradyne is one of the few employers on this list that states its office policy in writing, and across its postings that policy is on site five days a week. Who this is for: an embedded hardware engineer with real schematic and bring up hours, not a firmware engineer. The Qualcomm and NVIDIA platform note is the differentiator if you have it. Also note this is the same employer as two other roles on today's list, on different teams.
What the posting requires: over 7 years managing and maintaining distributed big data ecosystems, with the title stating a 7 to 11 year band. Strong Linux expertise including IP, iptables and IPsec. Scripting or programming in Perl, Golang or Python. Hands on experience with the Hadoop stack: HDFS, HBase, Airflow, YARN, Ranger, Kafka and Pinot. Familiarity with open source configuration management and deployment tooling such as Puppet, Salt, Chef or Ansible. Solid networking and open source fundamentals. DevOps tooling: SaltStack, Ansible, Docker and Git. Logging and monitoring: the ELK stack, Grafana, Prometheus, OpenTSDB and OpenTelemetry. Strong communication and collaboration. Nice to have: managing infrastructure on AWS, Azure or GCP; designing and reviewing system architectures for scale; and observability tooling for visualisation and alerting. The day to day: supporting incremental change across Linux and Unix environments; leading on call rotations, incident response, root cause analysis and postmortems; building automation for provisioning, scaling, upgrades and patching; capacity planning and performance tuning; enforcing security standards; and folding reliability practice into how product teams build. Benefits worth knowing: PhonePe publishes its full time benefits on the posting, including medical, critical illness, accident and life insurance, an employee assistance programme and on site medical centre, maternity and paternity benefits, adoption and day care support, relocation and transfer support, PF, gratuity, NPS, leave encashment and higher education support. Very few postings on this board list any of this. Who this is for: an SRE or infrastructure engineer who has actually operated Hadoop at scale, not just used it. If your big data experience is analytics rather than keeping clusters alive at three in the morning, this is not the fit.
What the posting requires: a bachelor's or master's in computer science, IT, AI or a related field. 8 or more years in IT engineering, of which at least 5 in IT automation and AI tooling solution and implementation. Note the title says Staff and the headline skill is automation, but the real floor is 8 years overall, not 5. Hands on experience shipping generative AI solutions with tools such as OpenAI, Microsoft Copilot, Claude, Cursor and GitHub Copilot. Proficiency in Python, Java or similar with the ability to build and integrate APIs and workflows. Working knowledge of AI and ML frameworks, prompt engineering, RAG patterns and agentic or workflow automation such as n8n or Zapier. Strong understanding of enterprise IT infrastructure, cybersecurity and cloud (Azure, AWS or Google Workspace). Experience with Microsoft 365, SharePoint and the Power Platform. Familiarity with IT security frameworks and identity tooling: LDAP, Entra ID, SSO and identity providers, VPNs. Exposure to SOC automation, AI driven ITSM or InfoSec response automation. The day to day: designing and maintaining reusable AI agents, workflows, MCP connectors and assistants; integrating them into enterprise IT and business systems; partnering with function leads to prototype and scale use cases; ensuring deployment meets Netradyne's responsible AI principles, GDPR obligations and InfoSec policy; supporting governance of generative AI tool budgets across the organisation; and monitoring and troubleshooting deployed automation. Location and office reality: Bangalore. Netradyne's stated policy across its postings is on site five days a week at Whitefield. Who this is for: an engineer who likes being a horizontal force multiplier and is comfortable working with every function in a company rather than one product team. If you want to go deep on one system, this is the wrong shape. If you have been the person quietly automating things for everyone and want that as the actual job description, it fits well.
What the posting requires: 8 or more years of software engineering experience. Deep understanding of distributed systems, database internals and network constraints, and clean maintainable code, with the posting stating you will be coding roughly 80 percent of the time. Extensive full stack experience with Python, Django, React or similar modern frameworks, and willingness to pick up whatever language the job needs. Hands on cloud and infrastructure experience: AWS, ECS and Docker, CloudWatch, particularly for data heavy or high throughput applications. A startup mindset, described as thriving in ambiguous zero to one environments with high velocity decision making. The day to day: owning features end to end across the stack; leading technical development of the Lens and Radiant platforms for data enrichment, labelling and continuous QA; architecting and scaling cloud environments and ECS services for video transcoding with telemetry across CPU, memory, network and disk IOPS; designing petabyte scale data pipelines; using agentic models as a force multiplier while making the architectural calls yourself; and mentoring mid and senior engineers through code review, pairing and architecture discussion. Location and office reality: Bengaluru, described as a hub the company is building out. Who this is for: a true generalist who is comfortable being the technical pillar of a small new team and does not want to specialise. The physical AI and robotics data angle is genuinely different from most listings here, so it suits someone who wants that domain. Backed by Benchmark, Spark Capital, Craft Ventures, Greylock and Y Combinator, if investor quality matters to your risk calculation.
What the posting requires: 8 or more years of software engineering experience with 4 or more 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, which ChargePoint specifies should be from what it calls a top tier institution. Deep expertise in Python, FastAPI, Django and modern backend frameworks. Hands on LLM engineering: LangChain, LangGraph, Bedrock or OpenAI APIs, prompt engineering and RAG. Strong Elasticsearch including vector search, hybrid search and semantic retrieval. Vector databases such as Qdrant, ChromaDB or Pinecone. Production LLM systems with low latency inference, caching and observability. Distributed systems design, microservices and event driven patterns with Kafka or RabbitMQ. Cloud (AWS or GCP), Docker, Kubernetes and CI/CD. Strong PostgreSQL including query optimisation and schema design, plus Redis and MongoDB. A track record of measurable performance improvements. Also listed: voice AI and telephony integration (Genesys, SIP) and speech pipelines; computer vision and visual transformers; data engineering with Airflow, DBT, ClickHouse, Trino and Iceberg; experience with datasets over 50TB; fine tuning with LoRA or QLoRA; RLHF style preference tuning; observability stacks; and certifications in generative or agentic AI. Location and office reality: the requisition header says India and the posting body states Bangalore, India. Who this is for: an engineer who has already put LLM systems into production and can talk about latency and cost rather than model choice. The requirement list is long and reads like several roles fused together, so expect to be strong in the LLM and search half and passable on the voice and vision half rather than expert in all of it.
What the posting requires: 8 or more years of engineering experience, extensively with Django or Flask, React and relational databases in a microservice architecture. A bachelor's in computer science or computer engineering preferred. Strong AWS experience across Route53, CloudFront, API Gateway, Aurora RDS, DynamoDB, ElastiCache, EKS, ECS, S3, the AWS SDK, Lambda and SQS. Proficiency writing unit and integration tests plus hands on CI/CD including Git, pipeline tooling and security scans. Linux administration with console commands, scripting and utilities in Python and BASH. Demonstrated REST API building with OpenAPI or Swagger specs. Agile development experience and familiarity with gRPC, GraphQL and automation tooling such as Ansible, Chef or Puppet. Third party integration and custom application development. SQL and NoSQL across MySQL, Postgres, Redis, DynamoDB, Elasticsearch and MongoDB. BI tooling such as Tableau or Power BI. The day to day: designing and maintaining cloud native solutions and analytics dashboards for proactive monitoring and network hygiene; documenting development and modification; ensuring data integrity and security; producing data flow and data structure diagrams; performing code reviews; and helping train and guide others through projects start to finish. Location and office reality: the requisition is tagged IN-Karnataka-Bangalore and the body states Bangalore, India. Who this is for: a backend engineer who is comfortable in the Python web stack and has real AWS breadth, and who cares about code quality standards enough to enforce them. The dashboards and BI tooling mention means part of the output is visible reporting, not just services.
What the posting requires: 8 to 12 years of software engineering experience with deep frontend expertise. Expert level JavaScript, TypeScript, HTML and CSS. Extensive React (or similar) experience 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 across teams. The day to day: defining and evolving frontend architecture patterns used across product teams; leading architecture reviews and guiding design decisions; driving adoption of shared platforms, frameworks and tooling to reduce duplicated effort; establishing engineering standards and decision frameworks; setting performance, accessibility and user experience standards; establishing testing, observability and monitoring practice; identifying systemic frontend risks and leading cross team efforts on technical debt; and mentoring senior engineers. Location and office reality: Pune, India. Who this is for: a senior frontend engineer who has already outgrown owning one application and wants to shape how several teams build. Be clear eyed about the influence without authority framing: the posting repeats it, which usually means the organisation knows it is the hard part of the job. If you prefer shipping user facing features, the day to day here is mostly standards, reviews and shared abstractions.
What the posting requires: a bachelor's or master's in computer science, information systems or a related field. 8 or more years in Salesforce development and enterprise application engineering. Strong hands on Apex, Lightning Web Components, JavaScript, Flows, SOQL, APIs and platform customisation. Strong understanding of Salesforce architecture, governor limits, declarative automation, integration patterns and scalable solution design. Experience with CI/CD, deployment processes, code refactoring and performance optimisation in Salesforce environments. Experience integrating Salesforce with enterprise systems using APIs, ETL tools and automation platforms. Salesforce Platform Developer II certification is strongly preferred, with JavaScript Developer, Advanced Administrator, Application Architect or System Architect certifications a plus. Good understanding of AI powered and agentic development tools such as Cursor, Claude Code and Agentforce. The day to day: developing, testing, documenting and deploying Salesforce solutions; supporting enhancements, break fix and ongoing maintenance; investigating technical and integration issues with development, operations and business teams; managing multiple priorities; researching new platform capabilities and prototypes; and mentoring junior engineers and administrators. How they measure you: MongoDB publishes ramp expectations on this posting. At three months you understand its Salesforce ecosystem and current implementations. At six months you have delivered one or more critical initiatives and become a trusted technical contributor. Location and office reality: MongoDB states it is looking to speak to candidates based in Gurugram for its hybrid working model, so this one is not remote. Who this is for: a Salesforce engineer, plainly. Strong general backend engineers without Apex and LWC depth will not clear the bar, and equally, this is a good seat if you have that depth and want it valued at a product company rather than at a consultancy.
What the posting requires: 9 or more years, stated directly in the job header. Demonstrated success driving organisation level architecture and multi team initiatives. Deep expertise in distributed systems, scalability and data platforms. Ability to convert ambiguous business and regulatory requirements into system architecture. Proven ability to influence across teams without authority. Strong storytelling and stakeholder management. The posting frames these as all Staff requirements plus the above, so expect to be assessed against the Staff bar first. Nice to have: experience building enterprise grade compliance systems. The day to day: defining long term platform architecture; leading cross organisation programmes across engineering, product and compliance; shaping architectural frameworks and standards used by other teams; partnering with directors, engineering managers and product or compliance leadership on strategy; architecting high scale ingestion for billions of events a day; leading migrations and re architectures; setting SLOs and driving resilience, data quality and observability work; leading design reviews and technical councils; and mentoring Staff and Senior engineers. Location and office reality: Netradyne publishes this clearly, which almost nobody else does. Whitefield, Bangalore. Full time. Work model on site, five days in office. General shift. If you need hybrid, this posting has already answered you. Who this is for: an architect who is genuinely energised by influence work. Read the responsibilities honestly before applying: the coding content is not spelled out and the described output is architecture, standards, reviews and cross team programmes. It reports alongside directors and engineering managers rather than into a single team.
What the posting requires: 9 or more years building production grade distributed systems in Java, Scala, C++ or Go. A proven track record architecting solutions for large scale infrastructure and cloud compute. The role is described as technical lead for the Bengaluru chapter, defining technical strategy for problems where the solution is not yet known. The day to day: architecting systems to optimise cloud spend at very large scale; defining the roadmap for the efficiency pillar and running design reviews and risk assessments; building regression detection and automated resource rightsizing; building the frameworks that let product teams measure their own efficiency footprint, and the automated release gates that hold them to it; acting as technical authority during incidents involving system wide performance issues; mentoring junior and senior engineers; and designing the AI driven detection, decisioning and autonomous remediation layers that let cost governance run continuously. Location and office reality: Bengaluru, India. Databricks describes itself as still building out this office, so expect a growing team rather than an established one. Who this is for: a distributed systems engineer who finds infrastructure economics interesting rather than tedious. It is a good seat if you want measurable impact you can point at in a performance review, since the output is denominated in dollars saved. The founding engineer framing means more ambiguity and more say in direction than a typical Staff role.
What the posting requires: 10 or more years of work experience in endpoint, network or cloud security product development. Strong C++ programming. Expertise in data structures and algorithms. Deep understanding of TCP/IP networking protocols. Deep understanding of macOS internals and experience developing software on macOS. Knowledge of cryptography techniques. Experience writing multi platform code. Familiarity with web data formats such as JSON, XML and MIME. Knowledge of CI/CD tooling such as Jenkins. Strong written and verbal communication. A BS in computer science is required and an MS is strongly preferred. The day to day: building macOS client security endpoint agent technology; writing multi threaded and multi platform C++; taking requirement specs through research, design and implementation with attention to reliability, sustainability, scalability and observability; writing and running unit tests for your modules; working with product management on requirements; and helping QA test the product properly. Location and office reality: Bengaluru, Karnataka. Netskope's India engineering office. Who this is for: a systems programmer with actual macOS internals depth. This is one of the narrower asks on today's board and general C++ experience without the platform specialism will not carry it. Netskope has a matching Windows client role on this same list at 12 or more years, so if your depth is on the other platform, apply to that one instead.
What the posting requires: a bachelor's degree in computer science or a related field. 10 or more years of software development experience, stated in the job header. Hands on experience with embedded systems, Linux kernel device driver development or operating systems. Hands on hardware bring up using USB, ADC, GPIO, SPI, I2C, Wi-Fi and similar peripherals. Proficiency in embedded C and shell scripting, with Python scripting listed as an added advantage. Strong problem solving and the ability to work independently. Nice to have: prior experience at product or SaaS companies, ability to contribute individually while mentoring juniors, and familiarity with agile methodologies. The day to day: designing and implementing software in C and shell; leading code reviews and mentoring junior engineers; working with product managers on requirements; troubleshooting and debugging complex production issues; and implementing development best practice. Location and office reality: HM Tech Park, Whitefield, Bangalore. Full time. On site five days a week, stated in the posting. Who this is for: an embedded engineer who has actually written or ported kernel drivers, not an application developer who has used embedded Linux. If you have done bring up on real silicon, this is a strong match. Netradyne also has a hardware design role and a platform architecture role on today's list, on different teams, so pick the one that matches where you sit in the stack.
What the posting requires: a bachelor's or master's in computer science, engineering or a related field, with 10 or more years of enterprise integration experience including significant time in lead or architect roles. At least 5 years hands on designing and delivering complex enterprise grade integration solutions with Workato, with understanding beyond the low code surface: advanced recipes, callable recipes and event streams. Experience with event driven integration on Kafka or equivalent, including topics, producers and consumers, durability and retries. RESTful API design plus MCP based interfaces, OAuth2 and JWT, versioning and lifecycle management, and API management platforms such as Apigee. The day to day: leading architecture, design and implementation of Workato integrations and APIs across go to market systems; defining integration standards and best practices; designing and reviewing event driven workflows; translating ambiguous cross functional requirements into technical designs; mentoring other integration engineers and running design and code reviews; partnering with go to market, finance, data and security teams on governance, compliance and audit requirements; setting and enforcing non functional requirements for performance, resilience, observability and security; deep root cause analysis across systems; running proofs of concept; and participating in the on call and support rotation. Location and office reality: MongoDB states it wants candidates based in Gurugram for its hybrid working model. Not remote. Who this is for: an integration architect, and specifically one with real Workato depth. Note the on call expectation, which is unusual to see stated on an enterprise systems role and tells you these integrations are treated as production systems.
What the posting requires: a BS or higher in computer science or a related field. 12 or more years of production level experience in Python, Java, Scala, C++ or a similar language. 6 or more years developing large scale distributed systems from scratch. Experience working on a SaaS platform or with service oriented architectures. Experience on infrastructure related projects is listed as a plus. The day to day: working across problems that span product and infrastructure, including distributed systems, service architecture and monitoring at scale, workflow orchestration and developer experience; delivering services and client libraries for cloud storage backends; and building scalable services in Scala on Kubernetes with Spark data pipelines behind the pricing infrastructure. Location and office reality: Bengaluru, India. Who this is for: a senior distributed systems engineer. Note the gap between the two figures: 12 years total but only 6 building distributed systems from scratch, so a long career with a solid distributed systems core clears this even if the early years were elsewhere. Databricks has two other roles on today's list at 8 and 9 years, so if 12 is out of reach, look at those instead. The 14 new teams note means the specific team may be decided during the process rather than before it.
What the posting requires: 12 or more years of work experience in endpoint, network or cloud security product development. Strong C++ programming. Expertise in data structures and algorithms. Deep understanding of TCP/IP networking protocols. Deep understanding of Windows internals and working experience creating software on Windows. Knowledge of cryptography techniques. Experience writing multi platform code. Familiarity with web data formats such as JSON, XML and MIME. Knowledge of CI/CD tooling such as Jenkins. Strong written and verbal communication, described as open, transparent and consistent. A BS in computer science is required and an MS is strongly preferred. The day to day: building Windows client security endpoint agent technology; writing multi threaded and multi platform C++; taking requirement specs through research, design and implementation with attention to reliability, sustainability, scalability and observability; writing and executing unit test routines; working with product management on requirements; and supporting QA. Location and office reality: Bengaluru, Karnataka. Who this is for: a Windows systems programmer with kernel or driver level depth in security or networking software. If your background is macOS instead, Netskope's macOS client role is on today's list at 10 or more years. Both are on the same team, so applying to the one that matches your platform is better than applying to both.
What the posting requires: a bachelor's or master's in computer science, IT or a related field. 15 or more years securing complex on premises or cloud deployments, with a minimum of 6 years dedicated to cloud security architecture and design, including significant experience across AWS, GCP or Azure. Deep technical understanding of core cloud service models including compute, network and storage. Proficiency in at least one programming or scripting language such as Python, Go or Java for automating security tooling. Extensive experience with containerised applications (Kubernetes, Docker), CI/CD pipelines and microservices. 5 or more years with infrastructure as code for complex systems using Terraform, Ansible or similar. Demonstrated ability to explain complex technical issues to both specialists and non technical stakeholders. The day to day: defining and implementing cloud security architecture frameworks and guidelines; prioritising security maturity initiatives with cross functional teams; designing scalable solutions with cloud security architects, developers and engineers; building proofs of concept, tools and platforms; running architecture reviews, security assessments, threat modelling and risk analysis; establishing secure reference architectures and reusable patterns; strategic planning for cloud security capability including native and third party tooling; and partnering with incident response and SOC analysts. Location and office reality: Bangalore, India. Who this is for: a cloud security architect deep into a career, who still wants to build. One practical note: Rubrik's careers site rejects 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.
What the posting requires: strong Python with hands on FastAPI, Django, Flask or similar. Deep understanding of HTTP, WebSockets and gRPC. Proven experience building low latency distributed backend systems. Hands on experience with PostgreSQL, Redis, ClickHouse or related data systems. Familiarity with Kafka or Redis Streams. Solid understanding of API authentication, authorisation and security practice. Experience with Docker, Kubernetes and CI/CD. Hands on experience with at least one major cloud platform, with Azure preferred. Nice to have: canary deployments, progressive rollouts or feature flag systems; prior work on ML inference or model serving infrastructure; observability tooling such as Prometheus, Grafana and OpenTelemetry; and open source contributions or a solid GitHub portfolio. The day to day: designing and optimising Python APIs for serving ML models at scale; building communication layers over HTTP, WebSockets and gRPC; architecting low latency, fault tolerant and secure backends for real time inference; implementing authentication, rate limiting and request prioritisation; integrating voice agent and LLM SDKs; working with PostgreSQL, Redis and ClickHouse; building event driven and streaming architectures on Kafka and Redis Streams; and working on canary deployments and CI/CD. Location and office reality: Bengaluru. ⚠️ Years of experience: Sarvam publishes no experience figure anywhere in this posting. We write no number rather than guessing one, which means this role will not appear if you filter the board by years. Judged by the requirement list it reads mid to senior, but that is our reading and not the employer's statement. Who this is for: a Python backend engineer who wants latency and reliability problems rather than CRUD, and who is interested in AI infrastructure without needing to be a researcher. The posting describes a high talent density team with high ownership from day one, which usually means a demanding pace.
What the posting requires: experience owning product or platform systems end to end across multiple engineering and product teams at staff level. Strong fullstack 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 across multiple deployment environments. The day to day: architecting how data is ingested, modelled and synchronised into the Knowledge Graph; coordinating integration with Jira, observability tools, Zendesk and ServiceNow; designing the data marketplace for Snowflake, Databricks and BigQuery; publishing observability data as OpenTelemetry and supporting the access APIs; defining operational readiness across GitLab.com, Dedicated and Self-Managed; turning ambiguous product problems into technical plans with Product and Design; coordinating with the graph backend, AI platform and infrastructure teams; and mentoring senior and intermediate engineers. Location and office reality: listed as Bangalore, India. GitLab is a remote first company, but this particular requisition carries a Bangalore location rather than the Remote tag its other postings use, so confirm the arrangement with recruiting rather than assuming. ⚠️ Years of experience: GitLab does not publish a years figure on any of its postings, including this one. We write no number rather than inventing one, so this role will not appear under any experience filter. The Staff title and the end to end ownership language are the only level signals available. Who this is for: a fullstack engineer with genuine data platform depth. GitLab also states that all team members are expected to use AI in their daily workflow, which is a cultural expectation worth knowing before you apply.
What the posting requires: senior full stack development experience with a strong product orientation and a rigorous test first mindset. React and Next.js on the frontend. Ownership of the full delivery lifecycle: building features, defining test cases, running deployments and validating production readiness. Comfort using AI agents and automation to generate test coverage at scale while owning the calls the tooling cannot make. Willingness to commit to sprint and release deadlines and raise risks early. The day to day: designing, building and maintaining full stack features across the Aedeon frontend with a focus on reliability, performance and user experience; working with product management, designers and backend or DevOps engineers to take features from requirement to tested release; participating in sprint planning, backlog grooming and retrospectives; owning delivery end to end including post release validation; and coordinating with DevOps and QA so the deployment pipeline is clean and repeatable. The interview process, which Mactores publishes: a panel interview, described as a structured conversation with members of the hiring team covering your experience, product thinking and how you work. The posting also asks you to answer as many application questions as possible to speed things up. Very few employers on this list tell you the process in advance. Location and office reality: Mumbai, Maharashtra. ⚠️ Years of experience: Mactores publishes no figure. The posting says senior, and we write no number rather than guessing, so this role will not appear under an experience filter. Who this is for: a product minded full stack engineer who wants ownership of releases and is genuinely comfortable with an AI heavy workflow. The posting reads as a demanding delivery culture, and it says so openly, which is better than finding out later.
What the posting requires: experience building and shipping agentic or conversational AI systems in production rather than prototypes. Strong intuition for where LLM behaviour breaks down under real world conditions and how to fix it systematically. Systems thinking that treats conversation architecture, evaluation, serving infrastructure and candidate experience as one problem. Care about the quality bar at the level of a user who depends on the output rather than a researcher measuring aggregate metrics. The day to day: architecting and developing Chakra end to end, covering agent design, conversation management, real time response evaluation, scoring methodology and report generation; building the infrastructure that keeps the 200,000th interview as coherent as the first; designing evaluation and benchmarking pipelines for interview quality, candidate experience consistency and report defensibility; building fine tuning and RLHF workflows to push model judgment past off the shelf behaviour; defining and instrumenting the quality bar; and working across data pipelines, model serving, latency constraints and the product experience itself. Location and office reality: hybrid in Bengaluru, India. ⚠️ Years of experience: HackerRank publishes no figure on this posting. We write no number rather than guessing, so it will not appear under an experience filter. The requirement to have shipped production agentic systems is the real gate, and that tends to imply several years. Who this is for: an ML engineer who has taken LLM systems past the demo stage and has opinions about evaluation. If your experience is model training rather than production behaviour and guardrails, the emphasis here is on the latter. There is a second HackerRank ML role open on the evaluation side if this specific product does not appeal.
What the posting requires: 5 or more years in technical support, product operations, technical account management or engineering, with a specific focus on complex technical products such as APIs, SaaS or telecommunications. Experience in the technology industry including APIs and VOIP, in either a development or support capacity. 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 influence skills, including the ability to negotiate prioritisation of supportability features with technical stakeholders. Familiarity with customer trust applications is preferred. Nice to have: project management methodology or experience managing programmes and product launches; proficiency in a scripting or programming language such as Python, Java or Node.js to better understand the developer experience; and knowledge of design thinking. The day to day: embedding supportability requirements into the earliest stages of the product development lifecycle through design reviews and technical planning with R&D; analysing support data to build business cases that influence what R&D prioritises; specifying proactive product features that deflect support tickets; orchestrating global operations readiness for new feature launches; and translating complex customer use cases into requirements. Location and office reality: the posting states directly that the role is remote and based in India, with no state restriction listed on this requisition. Twilio describes itself as remote first. Note that some other Twilio India postings do restrict which states you can live in, so confirm during the process. Who this is for: someone who has done deep technical support or technical account management on an API product and wants to influence the product rather than keep absorbing its rough edges. Twilio explicitly encourages applicants whose careers have not followed a traditional path. This is not a coding role, though scripting familiarity helps.
What the posting requires: 8 or more years designing, building and scaling data, machine learning and AI systems on premises and in the cloud using Python, Scala and Java in production, with expertise in machine learning or generative AI. Experience with AWS, Azure or GCP, with Databricks familiarity a plus. Proficiency in the data engineering needed to orchestrate end to end ML training pipelines, ideally processing large datasets with Apache Spark. Subject matter expertise in feature engineering, ML frameworks, model training, monitoring, drift detection and retraining. Proficiency with algorithms, deep learning and NLP techniques. Prior experience building, designing or troubleshooting LLM based generative AI applications. Familiarity with agentic frameworks such as LangChain and LangGraph. Expertise in context orchestration including prompt design, memory management, retrieval systems, vector embeddings, semantic search and tool integrations. Comprehensive MLOps and LLMOps knowledge. Prior support or customer facing experience. The day to day: acting as senior technical expert on complex issues spanning data pipelines, ML pipelines and AI applications; troubleshooting production workloads at code level; diagnosing ML and LLM deployments including inference, autoscaling, monitoring and alerting; guiding customers on model lifecycle and observability; supporting generative AI use cases across RAG, agents, vector search and prompt engineering; and collaborating internally to influence the roadmap and contribute documentation. Location and office reality: Bengaluru, India. Who this is for: an ML engineer who genuinely enjoys debugging other people's systems and talking to customers while doing it. This is a support engineering seat, not a platform building one, but the technical bar is the same. Readers asked for customer facing technical roles by name, and this is one of the more hands on examples on today's list.
What the posting requires: 8 or more years of technical, partner facing experience, and the posting names Systems Engineer, Solutions Architect or Technical Account Manager as the shapes it means, in cybersecurity, cloud infrastructure or networking. Strong technical depth in Cloudflare One or equivalent SASE and SSE architectures, zero trust, DNS and application security, plus hands on familiarity with AI deployment, AI Gateway, LLM orchestration frameworks or vector databases. A proven track record developing technical talent or building champion programmes inside partner organisations. Deep understanding of enterprise IT and multi cloud and hybrid environments, with complex multi stakeholder project management. Demonstrated ability to manage the technical lifecycle of a deal from pre sales discovery through post sale delivery. Strong communication, presenting complex architectures to both partner leadership and engineers. A bachelor's in computer science or engineering, or equivalent practical experience. The day to day: owning the technical relationship with assigned partners and building joint go to market plans; enabling partners to lead their own technical discovery and architecture; cultivating technical champions; owning the technical account plan; co developing joint service catalogues and managed SASE practices; acting as escalated technical contact for architectural health; and using Cloudflare's own AI tooling to automate repeatable technical work. Location and office reality: available locations are listed as Bengaluru, India and India, with the requisition marked hybrid or remote. One of only three roles on today's list with any remote option. Who this is for: a solutions engineer or technical account manager with real network and security depth. Be clear that this is a partner facing commercial role: it involves pre sales work and pipeline influence, and the posting says so. It passes the technical bar because the requirements demand hands on architecture and platform knowledge, but if you want to write code all day this is not that job.
What the posting requires: 12 or more years in a customer facing technical role, including significant pre sales, consulting, partner or solutions architecture experience in enterprise software. Strong experience navigating complex sales cycles and aligning technical and business stakeholders. Hands on experience with modern application development, data platforms or cloud native systems, including at least one scripting or programming language such as Python, JavaScript, Java, C# or SQL. Experience designing distributed systems in cloud and hybrid environments with an understanding of scalability, resilience and security. The ability to translate technical architecture into business value for executives, architects and developers. Experience in one or more of hyperscaler partnerships, ISV integrations, AI and ML applications, data engineering, platform modernisation or developer platforms. Demonstrated ability to create technical assets and lead workshops. The day to day: designing architectures on MongoDB Atlas for customer and partner led solutions; acting as trusted technical advisor through architecture reviews and modernisation strategy; working complex partner opportunities through discovery, demos, proofs of value and sizing; building joint partner offerings and reference architectures; creating reusable field assets; advising on RAG, vector search and agentic workflows; relaying field feedback to product and engineering; supporting territory and account planning; representing MongoDB at workshops and industry events; and mentoring peers. Location and office reality: India, on MongoDB's remote working model, stated in the posting. Who this is for: a senior solutions architect who wants the partner ecosystem rather than direct accounts, and who values working from anywhere in India. The coding requirement is real but light: one language, used to build demos and assets. At 12 or more years this is aimed well into a career.
What the posting requires: a customer facing technical lead with enough full stack depth to configure, debug and explain web applications and integrations, and to generate API scripts as needed in Ruby or Python. Confidence leading onsite conversations with prospects and enterprise customers while gathering requirements and shaping technical approaches. Clear communication that can go deep with engineers or simplify for non technical audiences. Strong operational discipline in planning, executing and following through. Nice to have: experience as a software, solutions or sales engineer working with HR technology, applicant tracking systems, IDEs, developer tools, or API first and integration heavy systems; and a track record of taking projects from scoping through delivery. The day to day: leading customer facing engagements including discovery, pilots and demos as the primary technical voice; partnering onsite with customers to uncover developer needs and shape solutions; keeping projects on track through disciplined execution and proactive updates; using AI tooling where it delivers faster and more reliable outcomes; and collaborating with product, engineering and go to market teams to represent the customer. Location and office reality: hybrid in Bengaluru, India, with the role itself involving onsite work at customer locations. Expect travel. ⚠️ Years of experience: HackerRank states no figure on this posting. We write no number rather than guessing, so it will not appear under an experience filter. Who this is for: an engineer who likes customers and variety and does not want a single codebase. Readers asked for technical account management and customer success roles by name, and this is one of the more technical versions of that shape. If being onsite at a customer site regularly does not appeal, skip it.
What the posting requires: significant experience in field engineering, solution architecture or enterprise platform deployment, with a track record owning senior technical relationships. Deep expertise in enterprise fleet automation, specifically Python and PowerShell scripting at production scale across provisioning, diagnostics and remediation. Advanced proficiency with Intune, SCCM and enterprise MDM architecture. Experience with cross OEM hardware interoperability and platform level troubleshooting. The day to day: owning the technical relationship with strategic enterprise accounts from architecture through deployment and ongoing platform health; leading solution architecture for on device AI on AI-PC platforms including NPU offload design and SLM configuration; owning end to end escalation delivery for the most complex platform, firmware and fleet issues; building fleet automation frameworks; driving cross OEM interoperability directly with hardware partners; defining deployment architecture standards and runbooks; acting as the field to product conduit; leading technical presales including architecture reviews, proof of concept design and executive level presentations; and mentoring other forward deployed engineers. Location and office reality: Bengaluru. ⚠️ Years of experience: Sarvam publishes no figure. The Principal title and the description of it as the most senior IC seat in the function are the only level signals. We write no number rather than guessing, so it will not appear under an experience filter. Who this is for: a field or platform engineer with genuine Windows endpoint management depth, Intune and SCCM specifically, who wants that skill applied to on device AI rather than corporate IT. The presales element is real, so expect executive conversations alongside the debugging. It is a demanding, autonomous seat and the posting does not pretend otherwise.