Senior Software Engineer (AI)

Location: Hybrid; presence required 4 days per week in the San Francisco, San Jose, or Bellevue office. Tuesday is the designated work-from-home day.

Annual salary: $255,000–$346,000 in San Francisco/San Jose; $230,000–$311,000 in Bellevue.

Company

Lambda builds AI cloud infrastructure for researchers, enterprises, hyperscalers, and large-scale machine learning workloads.

What you will do

• Design and maintain scalable control-plane services, operators, and custom Kubernetes controllers.
• Develop Go and Python automation for cluster provisioning, upgrades, patching, and deletion.
• Build GPU-aware orchestration for scheduling and resource allocation across AI workloads.
• Integrate networking technologies including Cilium, Multus, InfiniBand, RoCE, RDMA, and GPUDirect.
• Develop inference platform services, autoscaling systems, multi-model deployment patterns, and internal deployment and monitoring tools.
• Support production systems through debugging and an on-call rotation.

Requirements

• 6+ years of software engineering experience and ownership of significant technical scope.
• Deep knowledge of Kubernetes internals, including controllers, schedulers, operators, CRDs, CSI, CNI, and control-plane components.
• Strong understanding of distributed systems, fault tolerance, graceful degradation, and failure handling.
• Strong programming skills in Go and Python, with solid knowledge of Linux, networking, containers, and cloud infrastructure.
• Experience with observability at scale, including Prometheus, Grafana, distributed tracing, and actionable alerting.
• Ability to work from the required United States office location on the hybrid schedule.

Nice to have

• Experience building managed Kubernetes services such as GKE, EKS, or AKS.
• Hands-on experience with NVIDIA GPU and networking technologies, including GPU Operator, device plugins, DCGM, MIG, Network Operator, and NCCL.
• Familiarity with Slurm, KAI, Volcano, Kueue, InfiniBand, RDMA, high-performance computing, and AI/ML storage architecture.
• Contributions to CNCF projects or Kubernetes SIGs.

Culture & Benefits

• Work on core infrastructure used by AI research labs, enterprises, and hyperscalers.
• Collaborate across Kubernetes, networking, storage, compute, ML, and infrastructure teams.
• Generous cash and equity compensation.
• Health, dental, and vision coverage for employees and dependents.
• Wellness and commuter stipends for select roles, a 401(k) plan with a 2% company match for US employees, and flexible paid time off.