Highly Skilled Kubernetes Engineer

11 hours ago

Solapur, Maharashtra, India beBeeKubernetes Full time ₹ 1,50,00,000 - ₹ 2,25,00,000

We are looking for a highly skilled engineer to join our team. As a Senior Kubernetes Platform Engineer, you will design and implement the Zero-Touch Build, Upgrade, and Certification pipeline for our on-premises GPU cloud platform.

Key Responsibilities:
  • Architect and implement GitOps-driven Kubernetes cluster lifecycle automation using tools like kubeadm, ClusterAPI, Helm, and Argo CD.
  • Develop and manage declarative infrastructure components for GPU stack deployment (e.g., NVIDIA GPU Operator), container runtime configuration (Containerd), and networking layers (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.
  • Drive observability, testing, and validation as part of the continuous delivery process (e.g., cluster conformance, GPU health checks).
  • Collaborate with infrastructure, security, and SRE teams to ensure seamless handoffs between lower layers (hardware/OS) and the Kubernetes platform.
  • Mentor junior engineers and contribute to the platform automation roadmap.
Requirements:
  • 10+ years of hands-on experience in infrastructure engineering, with a strong focus on Kubernetes-based environments.
  • Primary key skills required are 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, and 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.
  • Bonus: Experience with custom controllers, operators, or Kubernetes API extensions, contributions to Kubernetes or CNCF projects, exposure to service meshes, ingress controllers, or workload identity providers.

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