Validation & Performance Automation Engineer

ob Description:

Position:

Senior Infrastructure Test & Validation Engineer

stability, performance, and conformance

strong infrastructure background

Key Responsibilities

• Design and implement

  GitOps-compliant 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 under 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 comprehensive test coverage across

  conformance, performance, fault injection, and post-upgrade validation

  .
• Build and maintain dashboards and reports 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 & Experience

• 10 years

  of hands-on experience in

  infrastructure engineering, systems validation, or SRE

  roles.

• Primary skills:

  pytest, Go, k6, scripting, automation frameworks, integration, Sonobuoy, LitmusChaos, CI integration.
• Strong experience with:

• Sonobuoy

  – Kubernetes conformance and diagnostics.

• LitmusChaos

  – Fault injection and resilience validation.

• k6

  – 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., Argo CD, Flux).
• Hands-on experience with CI/CD systems (e.g., GitHub Actions, GitLab CI, Jenkins) to automate test orchestration.
• Strong scripting and automation skills in

  Python, Bash, or Go

  .
• Familiarity with

  GPU-based infrastructure

  and its performance characteristics is a strong plus.
• Excellent

  debugging, root cause analysis, and incident investigation

  skills.