Cloud Automation Specialist

2 days ago

Madurai, Tamil Nadu, India beBeeEngineer Full time ₹ 15,50,000 - ₹ 23,25,000

We are seeking a highly skilled and experienced Infrastructure Test & Validation Engineer to lead the Zero-Touch GPU Cloud platform.

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Key Responsibilities

• Design, implement and orchestrate automated validation pipelines using GitOps workflows for validation and certification of the entire stack—from hardware to Kubernetes.

• Integrate Sonobuoy for Kubernetes conformance and certification testing.

• Design 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 comprehensive 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.

Requirements:

• 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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