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Urgent! K8s lifecycle automation eng Job Opening In Bengaluru – Now Hiring LTIMindtree

K8s lifecycle automation eng



Job description

Job Description: Senior Kubernetes Platform Engineer (Zero-Touch GPU Cloud – Git Ops 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% Git Ops 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 Git Ops-driven Kubernetes cluster lifecycle automation using tools like kubeadm , Cluster API , 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 Git Ops integration, Go/Python scripting, Containerd
Deep knowledge and hands-on experience with:
Kubernetes cluster management (kubeadm, Cluster API)
Argo CD for Git Ops-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 Git Ops 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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