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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 with observability and metrics tooling such as Prometheus, Grafana, Datadog or ElasticSearch. - 3+ years working with data querying and pipelines such as SQL, Airflow, Trino or SQS. - Working knowledge of network fundamentals and hardware, for example Cisco and Palo Alto. - Experience with Infrastructure as Code. - Hands on experience with CI/CD and automation tooling such as Jenkins, ArgoCD or GitHub Actions, across AWS, GCP or Oracle Cloud. - Comfort working in ticket and workflow driven environments using Jira and Confluence. Nice to have: - Experience supporting enterprise SaaS tools such as Salesforce and Workday, and SSO or identity integration such as Okta. What the work actually looks like: - Manage the ticket queue, prioritise and resolve requests, and identify recurring categories to automate or deflect. - Take part in a rotating on call and incident response schedule, including weekends, troubleshooting and documenting in real time. - Build and maintain monitoring dashboards in Tableau, Superset and Grafana covering service health, availability and data quality. - Use AI assisted tools to speed up triage, root cause analysis, scripting and documentation, while knowing when a problem needs hands on judgement instead. - Write and maintain automation code in Python, Go, JavaScript, TypeScript and Bash. - Partner with global stakeholder teams to drive issues to resolution. Location and working pattern: India remote, eligible anywhere within India. The posting says the role may include occasional work at an Airbnb office or attendance at offsites, as agreed with your manager. That is a genuinely remote posting rather than a hybrid one described loosely, which matters if relocation is the thing standing between you and a job. Honest fit guidance: this is an operations and reliability seat, not a product engineering one, and the weekend on call is stated up front. If you have three years in observability and pipelines and you want remote work in India, this is one of the few postings today that qualifies on both counts. No interview process is 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.