Cloud Infrastructure Validation Specialist

4 days ago

Ellore, Andhra Pradesh, India beBeeAutomation Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Senior Cloud Automation Engineer

We are seeking an experienced Senior Cloud Automation Engineer to lead our cloud infrastructure automation efforts. This role will focus on designing and implementing automated, GitOps-compliant pipelines for validation and certification of our GPU cloud stack.

Key Responsibilities:

  • Design and implement automated, GitOps-compliant 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.
  • 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.

Required Skills & Experience:

  • 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:
    • o Sonobuoy for Kubernetes conformance and diagnostics
    • o LitmusChaos for fault injection and resilience validation
    • o k6 for performance/load testing in distributed environments
    • o 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.
  • Strong debugging, root cause analysis, and incident investigation skills.

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