Highly Skilled Kubernetes Infrastructure Architect

1 week ago

Bellary, Karnataka, India beBeeKubernetes Full time ₹ 1,80,00,000 - ₹ 2,20,00,000
Job Opportunity

We are seeking a highly skilled Kubernetes Engineer to join our team. This is an exceptional opportunity for someone with extensive experience in designing and implementing cutting-edge Kubernetes-based infrastructure solutions.

About the Role

The ideal candidate will have 10+ years of hands-on experience in infrastructure engineering, with a strong focus on Kubernetes-based environments. They will be responsible for architecting and implementing GitOps-driven Kubernetes cluster lifecycle automation using tools like kubeadm, ClusterAPI, Helm, and Argo CD.

Key Responsibilities:
  • Automation Expertise: 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.), and lead automation efforts to enable zero-touch upgrades and certification pipelines for Kubernetes clusters and associated workloads.
  • Infrastucture Specialist: Maintain Git-backed sources of truth for all platform configurations and integrations.
  • Deployment Lead: Standardize deployment practices across multi-cluster GPU environments, ensuring scalability, repeatability, and compliance.
  • Oversight and Quality Assurance: Drive observability, testing, and validation as part of the continuous delivery process (e.g., cluster conformance, GPU health checks).
  • Collaboration: Collaborate with infrastructure, security, and SRE teams to ensure seamless handoffs between lower layers (hardware/OS) and the Kubernetes platform.
  • Talent Development: Mentor junior engineers and contribute to the platform automation roadmap.
Required Skills & Qualifications:
  • 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, and 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.
  • 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.

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