Lead Infrastructure Validation Specialist

7 days ago

Cochin, Kerala, India beBeeEngineer Full time ₹ 2,50,00,000 - ₹ 3,00,00,000
Job Opportunity: Experienced Engineer

We are seeking an experienced engineer to join our team in a challenging role.

  • Design and implement automated pipelines for validation and certification of the GPU cloud stack across hardware, OS, Kubernetes, and platform layers.
  • Integrate Sonobuoy for Kubernetes conformance and certification testing.
  • Design and orchestrate chaos engineering workflows using LitmusChaos to validate system resilience across failure scenarios.
  • Implement performance testing suites using k6 and system-level benchmarks, integrated into CI/CD pipelines.
  • Develop and maintain end-to-end test frameworks using pytest and/or Go, focusing on cluster lifecycle events, upgrade paths, and GPU workloads.

Key Responsibilities:

  • Ensure test coverage and validation across multiple dimensions: conformance, performance, fault injection, and post-upgrade validation.
  • Build and maintain dashboards and reporting for automated test results, including traceability, drift detection, and compliance tracking.
  • Collaborate with infrastructure, SRE, and platform teams to embed testing and validation early in the deployment lifecycle.
  • Own quality assurance gates for all automation-driven deployments.

Required Skills & Qualifications:

  • 10+ years of hands-on experience in infrastructure engineering, systems validation, or SRE roles.
  • Primary key skills required are pytest, Go, k6 scripting, automation frameworks integration (Sonobuoy, LitmusChaos), CI integration.
  • Strong experience with:
    • Sonobuoy for Kubernetes conformance and diagnostics.
    • LitmusChaos for fault injection and resilience validation.
    • k6 for performance/load testing in distributed environments.
    • pytest or Go-based test frameworks for automation and validation scripting.
  • Deep understanding of Kubernetes architecture, upgrade patterns, and operational risks.
  • Experience validating infrastructure components (GPU drivers, kernel modules, CNI, CRI, etc.) across lifecycle events.
  • Proficient in GitOps workflows and integrating tests into declarative, Git-backed pipelines (e.g., with Argo CD, Flux).
  • Hands-on experience with CI/CD systems (e.g., GitHub Actions, GitLab CI, Jenkins) to automate test orchestration.
  • Solid scripting and automation experience (Python, Bash, or Go).
  • Familiarity with GPU-based infrastructure and its performance characteristics is a strong plus.
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