K8S Lifecycle Automation Eng

Job Description: Senior Kubernetes Platform Engineer (Zero-Touch GPU Cloud – GitOps Automation) We are looking for a Senior Kubernetes Platform Engineer with 10+ years of infrastructure experience to design and implement the Zero-Touch Build, Upgrade, and Certification pipeline for our on-premises GPU cloud platform. This role focuses on automating the Kubernetes layer and its dependencies (e.g., GPU drivers, networking, runtime) using 100% GitOps workflows. You will work 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. - 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.) - 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. Required Skills & Experience - 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 - 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