Senior Engineer - QA Automation, Load & Reliability Strategy

Job Description

We are seeking a seasoned QA and reliability engineering leader to define and drive our automation-first quality strategy, deeply embedded in our CI/CD workflows and platform engineering culture. This role is core to delivering robust, single-click pipelines, high-reliability environments, and data-driven insights at scale. As a Senior Engineer, youll own strategy and execution for test automation, synthetic data generation, load and performance testing, resilience testing, and environment optimization across platform services. Your Role & Responsibilities Build and scale automated QA frameworks across services, APIs, and UI for platform-grade quality Drive test enforcement in single-click CI/CD pipelines using GitHub Actions, ArgoCD, Jenkins, or equivalent Define and implement automated test data creation strategies using factories, mocks, and synthetic data generation tools Design and manage on-demand performance and load test environments using tools like k6, JMeter, Gatling, or Locust Architect and orchestrate resilience, fault-injection, and chaos testing strategies for critical platform components Establish performance environment strategy for multi-tenant, scalable systems with dynamic test coverage Define and track SLOs, SLAs, and error budgets, collaborating with SRE and observability teams Drive shift-left testing practices and embed automated validations early in the development lifecycle Enable self-service quality tools for developers and platform teams to improve test feedback loops Continuously evolve NFR validation strategies to ensure performance, stability, and availability benchmarks are met Skills & Experience Required 6+ years in QA automation, reliability engineering, or platform QA roles Hands-on experience with automation frameworks: Playwright, Selenium, REST-assured, or similar Proven experience in load, stress, and chaos testing for cloud-native distributed systems Deep experience with test data strategy, including synthetic test data, mocking, and data anonymization Expertise with CI/CD tooling and integration of quality gates within pipelines (ArgoCD, GitHub Actions, Jenkins, etc.) Strong knowledge of cloud environments (GCP, Azure) and Kubernetes-based deployments Proficient with performance monitoring and observability stacks (Grafana, Prometheus, New Relic, etc.) Familiarity with contract testing, component testing, and non-functional validation techniques Nice to Have Experience working with multi-tenant systems and complex environment reduction strategies Knowledge of test virtualization or mock service generation for isolated testing Exposure to GenAI tools in test acceleration, log summarization, or automated test generation Prior contribution to chaos engineering frameworks like Gremlin, Litmus, ChaosMonkey or ChaosMesh