
Senior Cloud Platform Developer
2 weeks ago
We are seeking a seasoned expert in Kubernetes platform engineering to join our team.
Job Description:
Skillful Kubernetes Engineer
We need a skilled professional with extensive experience in designing and implementing Kubernetes platforms. Your primary focus will be on architecting and automating the Zero-Touch Build, Upgrade, and Certification pipeline for our on-premises GPU cloud platform.
Main Responsibilities:
- Design 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), and 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 & Qualifications:
- At least 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.
Benefits:
Other Opportunities:
This is an excellent opportunity for a highly motivated and experienced professional to make a significant impact on our organization's success.
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