Senior Software Engineer (Managed Kubernetes)

Join our team as a Senior Software Engineer specializing in Managed Kubernetes. In this role, you will design, build, and maintain scalable control plane services, operators, and custom Kubernetes controllers. You will also develop automation for end-to-end cluster lifecycle management and build GPU-aware orchestration systems. Additionally, you will partner with the Network team on networking solutions for AI workloads and write resilient systems that handle failure gracefully. You will also develop platform services for inference, build internal tools and CLIs, and support and debug production issues.

• Design, build, and maintain scalable control plane services, operators, and custom Kubernetes controllers; develop automation in Go/Python for end-to-end cluster lifecycle management.
• Build GPU-aware orchestration systems, working within the platform architecture to support GPU scheduling and resource allocation.
• Partner with the Network team on networking solutions for AI workloads: CNI integration (Cilium, Multus), high-performance fabrics (InfiniBand, RoCE), RDMA, and GPUDirect.

• Strong programming skills in Go and Python; ability to collaborate effectively on shared codebases
• Solid knowledge of Linux systems, networking, containers, and cloud infrastructure
• If you don’t meet all of these requirements but believe you may be a good fit, please still apply and provide a cover letter that helps us understand your experience and readiness for this role
• Experience with observability at scale: Prometheus, Grafana, distributed tracing, and building actionable alerting systems
• Take pride in owning and delivering core components of products and platforms
• Solid grasp of distributed systems fundamentals — fault tolerance, graceful degradation, and failure handling in large-scale environments
• Experience operating the control plane and low-level pieces of large-scale Kubernetes clusters
• Have 6+ years of experience in software engineering, with a track record of owning significant technical scope within a team (e.g., driving a project from design through production, or acting as a de facto tech lead on a workstream)
• Deep understanding of Kubernetes internals: controllers, schedulers, operators, CRDs, CSI, CNI, and the extension patterns that make Kubernetes powerful
• Past contributions to CNCF projects or Kubernetes SIGs a plus
• Exposure to storage architecture for AI/ML workloads
• Familiarity with GPU, InfiniBand, RDMA, or high-performance computing on Kubernetes
• Familiarity with HPC and traditional job schedulers (Slurm) and Kubernetes-native batch scheduling (KAI, Volcano, Kueue)
• Hands-on experience with NVIDIA's GPU/networking ecosystem: GPU Operator, device plugins, DCGM, MIG, Network Operator, NCCL tuning, or similar
• Experience building and operating managed Kubernetes services (GKE, EKS, AKS, or similar) or working on Kubernetes control plane components