Senior Software Engineer (Mk8S Control Plane)

Join Lambda, a company building the AI Cloud of the future. As a Senior Software Engineer on our Managed Kubernetes (Mk8s) team, you will shape the architecture, reliability, and automation of our Kubernetes-based infrastructure. You will work at the intersection of distributed systems, GPU-accelerated computing, and Cloud Native infrastructure to build reliable and performant systems for our customers.

• 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.

• Solid knowledge of Linux systems, networking, containers, and cloud infrastructure
• Strong programming skills in Go and Python; ability to collaborate effectively on shared codebases
• Solid grasp of distributed systems fundamentals — fault tolerance, graceful degradation, and failure handling in large-scale environments
• Deep understanding of Kubernetes internals: controllers, schedulers, operators, CRDs, CSI, CNI, and the extension patterns that make Kubernetes powerful
• Experience operating the control plane and low-level pieces of large-scale Kubernetes clusters
• 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
• 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)
• 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
• Past contributions to CNCF projects or Kubernetes SIGs a plus
• Familiarity with HPC and traditional job schedulers (Slurm) and Kubernetes-native batch scheduling (KAI, Volcano, Kueue)
• Familiarity with GPU, InfiniBand, RDMA, or high-performance computing on Kubernetes
• Experience building and operating managed Kubernetes services (GKE, EKS, AKS, or similar) or working on Kubernetes control plane components
• Exposure to storage architecture for AI/ML workloads
• Hands-on experience with NVIDIA's GPU/networking ecosystem: GPU Operator, device plugins, DCGM, MIG, Network Operator, NCCL tuning, or similar