K8S Lifecycle Automation Engineer

Rarr Technologies

10 - 20 years

15 - 20 Lacs

hyderabad bengaluru

Posted:-1 days ago| Platform:

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Skills Required

automation git cloud services packaging linux internals deployment infrastructure security python scripting

Work Mode

Work from Office

Job Type

Full Time

Job Description

We are looking for a skilled Senior Kubernetes Platform Engineer with 10 to 15 years of hands-on infrastructure engineering experience, focusing on Kubernetes and automation. The ideal candidate will have expertise in designing and implementing GitOps-driven Kubernetes cluster lifecycle automation.

Roles and Responsibility

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, container runtime configuration, and networking layers.
Lead automation initiatives to enable zero-touch upgrades and certification pipelines for Kubernetes clusters and workloads.
Maintain Git-backed sources of truth for all platform configurations and integrations.
Standardize deployment practices for multi-cluster GPU environments ensuring scalability, repeatability, and compliance.
Integrate observability, testing, and validation into continuous delivery, including cluster conformance and GPU health checks.

Job Requirements

Minimum 10 years of hands-on infrastructure engineering experience with a strong focus on Kubernetes.
Core expertise in Kubernetes API, Helm templating, Argo CD, GitOps integration, Go/Python scripting, and Containerd.
Deep knowledge of 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 in GPU workloads.
Experience deploying and managing NVIDIA GPU Operator or equivalent in production.
Strong understanding of CNI plugin ecosystems, network policies, and multi-tenant networking.
Proven track record with Infrastructure-as-Code using Git-based workflows.
Experience building Kubernetes clusters in on-premises environments (vs managed cloud services).
Solid scripting/automation skills (Bash, Python, Go).
Familiarity with Linux internals, systemd, and OS-level tuning for container workloads.
Experience developing custom controllers/operators or Kubernetes API extensions is a plus.
Contributions to Kubernetes or CNCF projects are a plus.
Exposure to service meshes, ingress controllers, or workload identity providers is beneficial.

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