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Mid-level SDET, metro locations, popular role and VC-backed startup create high applicant competition.
Highly specialized SRE, Kubernetes and chaos engineering skills reduce cross-industry portability.
Explicit 4–8 years plus mandatory Kubernetes, Python, and Go increases hiring filter strictness.
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Define and own the strategy for system-level validation and reliability across Kubernetes-based distributed systems.
Design and build scalable automation frameworks for API, integration, end-to-end testing, regression, and reliability pipelines.
Drive chaos engineering, failure injection practices, and partner with SRE and platform teams to improve system observability and testability.
4-8 years of industry experience in QA/Automation focusing on reliability engineering and system-level QA.
Strong coding skills in Python and Go are mandatory.
Deep expertise in Kubernetes internals, distributed systems, observability stacks, and incident handling.
Experience with multi-cloud environments (AWS, Azure, GCP), Kubernetes managed platforms (EKS, GKE), networking, chaos testing, and automation frameworks.
Experienced in reliability validation and system-level testing within large-scale distributed Kubernetes environments.
Technical leader capable of owning platform-wide reliability and driving cross-team initiatives.
Expertise in designing automation for continuous validation to reduce production incidents and improve failure detection and remediation.