Description

You will architect and automate GitOps-driven Kubernetes cluster lifecycles, focusing on GPU stack deployment and multi-cluster scalability.

This role is hybrid.

Responsibilities

• Implement declarative infrastructure components for GPU stack deployment, container runtime configuration, and networking layers.
• Lead automation efforts to enable zero-touch upgrades and certification pipelines for Kubernetes clusters.
• Maintain Git-backed sources of truth for all platform configurations and integrations.
• Standardize deployment practices across multi-cluster GPU environments to ensure scalability and repeatability.
• Drive observability, testing, and validation as part of the continuous delivery process.

Required Skills

• 10+ years of hands-on infrastructure engineering experience focused on Kubernetes.
• Deep knowledge of Kubernetes API, Helm templating, and Argo CD GitOps integration.
• Proficiency with Go or Python scripting for automation tasks.
• Hands-on experience with Containerd as a container runtime.
• Experience deploying and operating the NVIDIA GPU Operator in production.
• Solid understanding of CNI plugin ecosystems and multi-tenant networking in Kubernetes.
• Experience building and managing Kubernetes clusters in on-prem environments.
• Familiarity with Linux internals and OS-level tuning for container workloads.

Preferred Skills

• Experience with custom controllers, operators, or Kubernetes API extensions.
• Exposure to service meshes or workload identity providers.

Key Skills

Education

Any Gradute