About the Role We are seeking a Senior SDET Engineer with deep expertise in infrastructure reliability, chaos engineering, and performance testing. You will own the quality strategy for our backend systems — designing and executing test frameworks that stress our infrastructure to its limits before our users ever do. You will work closely with platform, SRE, and backend engineering teams to embed quality thinking at every layer of our stack. ​ Key Responsibilities • Lead the design and implementation of chaos, failure, and performance test frameworks targeting distributed backend systems and infrastructure. • Build and maintain CI/CD pipelines in Jenkins using Groovy-based DSL and scripted/declarative pipeline definitions. • Own infrastructure-level test environments using Kubernetes — spinning up, tearing down, and managing test clusters for reliability experiments. • Execute and automate chaos engineering scenarios: network partitions, node failures, pod evictions, resource exhaustion, and latency injection. • Design and run performance and load tests to identify bottlenecks, regressions, and capacity limits across services. • Develop failure testing strategies to validate system behavior under degraded conditions — partial failures, cascading failures, and data corruption scenarios. • Define quality metrics and SLOs for infrastructure reliability; report on test coverage and failure patterns to engineering leadership. • Mentor and guide junior QA engineers; champion a reliability-first quality culture across the engineering org. ​ Requirements Required Qualifications • Strong programming skills in Python for test automation, tooling, and scripting. • Proficiency in Groovy, particularly for Jenkins pipeline development (scripted and declarative). • Extensive hands-on Jenkins experience — pipeline authoring, plugin management, shared libraries, and CI/CD architecture. • Deep Kubernetes knowledge — deploying workloads, managing namespaces, configuring resource limits, and operating clusters for test environments. • Proven experience in chaos engineering: fault injection, resilience testing, and tools such as Chaos Monkey, Litmus, or Gremlin. • Hands-on performance testing experience: load generation, profiling, bottleneck analysis, and tooling (e.g., Locust, k6, Gatling, JMeter). • Experience designing failure test scenarios for distributed systems — covering partial outages, dependency failures, and data-path degradation. • Strong understanding of Linux, networking, and infrastructure fundamentals. Nice to Have • Experience with service meshes (Istio, Linkerd) for traffic shaping and fault injection. • Familiarity with observability tooling: Prometheus, Grafana, Jaeger, or OpenTelemetry for validating test outcomes. • Background in SRE practices: SLOs, error budgets, incident post-mortems. • Experience with cloud infrastructure testing on AWS, GCP, or Azure at the platform level. • Exposure to eBPF-based tools for low-level system observability during failure tests.