Senior Kubernetes Platform Engineer

About Company:
Our Client Corporation provides digital engineering and technology services to Forbes Global 2000 companies worldwide. Our Engineering First approach ensures we can execute all ideas and creatively solve pressing business challenges. With industry expertise and empowered agile teams, we prioritize execution early in the process for impactful results. We combine logic, creativity and curiosity to build, solve, and create. Every day, we help clients engage with new technology paradigms, creatively building solutions that solve their most pressing business challenges and move them to the forefront of their industry.

Job Title :
Senior Kubernetes Platform Engineer

Job Locations :
Bengaluru

Experience : 8+
years

Education Qualification :
Any Degree Graduation

Work Mode :
Hybird

Employment Type :
Contract

Notice Period :
Immediate - 10 Days

Job description

Job Summary:

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