Kubernetes Infrastructure Architect

1 day ago

Bengaluru, Karnataka, India beBeePlatform Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

We are seeking a seasoned Kubernetes Platform Engineer to join our team.

Job Description

The ideal candidate will have 10+ years of experience in infrastructure engineering with a strong focus on Kubernetes-based environments.

  • Kubernetes Cluster Management:
  • kubeadm, ClusterAPI

Key Responsibilities:

  1. Architect and implement GitOps-driven Kubernetes cluster lifecycle automation using tools like kubeadm, ClusterAPI, Helm, and Argo CD.
  2. Develop and manage declarative infrastructure components for GPU stack deployment (e.g., NVIDIA GPU Operator), Container runtime configuration (Containerd), Networking layers (CNI plugins like Calico, Cilium, etc.).
  3. Lead automation efforts to enable zero-touch upgrades and certification pipelines for Kubernetes clusters and associated workloads.
  4. Maintain Git-backed sources of truth for all platform configurations and integrations.
  5. Standardize deployment practices across multi-cluster GPU environments, ensuring scalability, repeatability, and compliance.
  6. Drive observability, testing, and validation as part of the continuous delivery process (e.g., cluster conformance, GPU health checks).
Required Skills & Experience
  • Strong understanding of Kubernetes API, Helm templating, Argo CD GitOps integration, Go/Python scripting, Containerd.
  • Deep knowledge and hands-on experience with Kubernetes cluster management (kubeadm, ClusterAPI), Argo CD for GitOps-based delivery, Helm for application and cluster add-on packaging, Containerd as a container runtime and its integration in GPU workloads.
  • Experience deploying and operating the 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 (vs. managed cloud services).
  • Proven ability to scale and manage multi-cluster, GPU-accelerated workloads with high availability and security.
  • Solid scripting and automation skills (Bash, Python, or Go).
  • Familiarity with Linux internals, systemd, and OS-level tuning for container workloads.
Benefits

This role offers a unique opportunity to work with cutting-edge technology and contribute to the development of innovative solutions. The ideal candidate will be motivated by the prospect of working on complex projects and collaborating with a talented team of engineers.

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