Senior Performance Engineer, Hyderabad-based

Location: Bengaluru, India We are looking for a Senior Performance Engineer (L3) with solid experience across performance testing and strong JMeter scripting skills. You will define performance requirements with product owners and developers, validate environment readiness, run load, stress, spike, and soak tests, find root causes through full-stack observability, and give engineering teams and leadership evidence for release decisions. You will also own the performance framework and its CI/CD pipelines, build dashboards in CloudWatch and Grafana, run chaos and fault-injection tests on AWS and Azure, and test front-end performance alongside server-side performance. This position is intended for Hyderabad-based candidates who are available to work from the office. The client operates a scaled Quality Engineering function across a broad technology landscape running primarily on AWS, with Azure as the secondary cloud. Most applications run on containers. Performance engineering covers load, stress, spike, and soak testing, full-stack observability, root cause analysis, and chaos and resiliency testing for distributed systems. Performance engineers own performance testing delivery across multiple applications, from requirements and environment readiness through execution, root cause analysis, and release-readiness reporting. Own performance testing delivery across multiple applications from requirements through execution analysis and reporting Define performance requirements with product owners and developers Validate environment readiness before each test cycle Build and maintain JMeter scripts workload models and test data in GitHub Use similar tools such as K6 Gatling NeoLoad or LoadRunner when applicable Own the performance test framework and its CI CD pipelines on GitHub Actions or an equivalent tool Run load stress spike and soak tests on containerized workloads Validate autoscaling caching load balancing and failover during performance testing Test front end performance alongside server side performance Build dashboards in CloudWatch and Grafana covering RUM APM infrastructure logs and traces Use Prometheus or OpenTelemetry data in observability dashboards Correlate New Relic and Google Analytics data with test runs Validate golden signals SLIs and SLOs Use observability data to pinpoint bottlenecks across application API database network and container layers Recommend tuning and scaling changes and validate them with repeat tests Run chaos and fault injection tests on AWS and Azure using native tooling Contribute reusable scripts dashboards and runbooks that explain each application's resiliency setup Track performance defects to closure in Jira Coordinate with developers and product teams on defect priority and impact Deliver test summary reports in Confluence with release readiness evidence for engineering teams and leadership Use AWS and Azure for deployment secrets database services and performance test infrastructure Senior-level performance engineering experience across multiple applications Strong JMeter scripting and workload modelling experience Experience maintaining scripts and test data in GitHub Hands-on experience with load, stress, spike, and soak testing Experience with CI CD integration of performance tests using GitHub Actions or equivalent tools Experience validating autoscaling, caching, load balancing, and failover on containerized workloads Experience with an APM or observability platform such as CloudWatch, Grafana, New Relic, or similar Experience validating golden signals SLIs and SLOs Strong root cause analysis and tuning skills across application, API, database, network, and container layers Experience with front-end performance testing alongside server-side testing Experience with chaos and fault injection testing Working knowledge of AWS and Azure Working knowledge of Docker and Kubernetes Working knowledge of distributed systems and resiliency patterns Experience with defect tracking and reporting in Jira and Confluence Ability to present findings to engineering and business stakeholders Experience working in Agile teams Experience working in DevOps environments Ability to communicate clearly with developers, product, and delivery teams Hands-on use of AI coding assistants such as GitHub Copilot Claude Code Cursor Codex or equivalent to write and generate load test scripts Familiarity with GenAI LLMs and agentic workflows for maintaining performance scripts Familiarity with RAG and MCP concepts for QE tooling and for generating test data for load scenarios Experience with service virtualization using WireMock or an equivalent tool Experience with Tableau or an equivalent reporting tool Experience with Azure Monitor