GPU Cloud Architect

7 days ago

India beBeeKubernetes Full time ₹ 20,00,000 - ₹ 25,00,000
Senior Kubernetes Platform Engineer

We are seeking a seasoned Senior Kubernetes Platform Engineer to spearhead the design and implementation of our on-premises GPU cloud platform.

  • Design and implement a Zero-Touch Build, Upgrade, and Certification pipeline for our GPU cloud platform.
  • Automate the Kubernetes layer and its dependencies using 100% GitOps workflows.
  • Collaborate across teams to deliver a fully declarative, scalable, and reproducible infrastructure stack from hardware to Kubernetes and platform services.
Key Responsibilities:
  • Architect and implement GitOps-driven Kubernetes cluster lifecycle automation using tools like kubeadm, ClusterAPI, Helm, and Argo CD.
  • Deploy the GPU stack (e.g., Container runtime configuration, CNI plugins like Calico, Cilium, etc.).
  • Lead automation efforts to enable zero-touch upgrades and certification pipelines for Kubernetes clusters and associated workloads.
  • Maintain Git-backed sources of truth for all platform configurations and integrations.
  • Standardize deployment practices across multi-cluster GPU environments, ensuring scalability, repeatability, and compliance.
Requirements:
  • ~8+ years of hands-on experience in infrastructure engineering with a strong focus on Kubernetes-based environments.
  • Primary key skills: Kubernetes API, Helm templating, Argo CD GitOps integration, Go/Python scripting, Containerd.
  • Deep knowledge and hands-on experience with Kubernetes cluster management (kubeadm, ClusterAPI), Helm for application and cluster add-on packaging, and NVIDIA GPU Operator or equivalent in production environments.
  • Solid understanding of CNI plugin ecosystems, network policies, and multi-tenant networking in Kubernetes.
  • Strong GitOps mindset with experience managing infrastructure as code through Git-based workflows.
  • Experience building Kubernetes clusters in on-prem environments versus managed cloud services.
  • Solid scripting and automation skills (Bash, Python, or Go).
  • Familiarity with Linux internals, systemd, and OS-level tuning for container workloads.

The ideal candidate will have a strong foundation in Kubernetes, infrastructure engineering, and automation. If you're passionate about designing and implementing cutting-edge infrastructure solutions, we encourage you to apply.

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