K8S Lifecycle Automation Eng

2 days ago

New Delhi, India LTIMindtree Full time

Job Description: Senior Kubernetes Platform Engineer (Zero-Touch GPU Cloud – GitOps Automation)We are looking for aSenior Kubernetes Platform Engineerwith 10+ years of infrastructure experience to design and implement theZero-Touch Build, Upgrade, and Certification pipelinefor our on-premises GPU cloud platform. This role focuses on automating the Kubernetes layer and its dependencies (e.g., GPU drivers, networking, runtime) using100% 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 implementGitOps-driven Kubernetes cluster lifecycle automationusing tools likekubeadm ,ClusterAPI ,Helm , andArgo CD . Develop and manage declarative infrastructure components for: GPU stack deployment (e.g.,NVIDIA GPU Operator ) Container runtime configuration ( Containerd ) Networking layers ( CNI pluginslike Calico, Cilium, etc.) Lead automation efforts to enablezero-touch upgrades and certification pipelinesfor 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 experiencein infrastructure engineering, with a strong focus on Kubernetes-based environments. Primary key skillsrequired are Kubernetes API, Helm templating, Argo CD GitOps integration, Go/Python scripting, Containerd Deep knowledge and hands-on experience with: Kubernetescluster management (kubeadm, ClusterAPI) Argo CDfor GitOps-based delivery Helmfor application and cluster add-on packaging Containerdas a container runtime and its integration in GPU workloads Experience deploying and operating theNVIDIA GPU Operatoror equivalent in production environments. Solid understanding ofCNI 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 managemulti-cluster, GPU-accelerated workloadswith 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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