Staff Software Engineer - Managed Kubernetes
Lambda· Data Center Business
Hybrid (San Francisco Office (Fremont St)), Hybrid (San Jose Office (First St)), Hybrid (Bellevue Office)$349k - $465kFull-timePosted 3w ago
About the role
Staff Engineer to lead development of Lambda's Managed Kubernetes platform and related orchestration services (Managed Kubernetes, Managed Slurm on Kubernetes, and higher-level platform services for inference and AIOps) on bare metal GPUs. Role emphasizes technical leadership, cross-functional integration, and building scalable, multi-tenant cloud infrastructure for AI workloads.
Responsibilities
- Drive technical vision for Lambda's Managed Kubernetes bare-metal platform, including control plane scalability, multi-tenancy, cluster lifecycle management, and high availability
- Integrate and extend NVIDIA's open-source ecosystem: GPU Operator, Network Operator, DCGM, NCCL, and emerging projects like AICR and Topograph for topology-aware scheduling and placement
- Design GPU-aware orchestration systems
- Lead development of services that power our managed services
- Inform on and help with networking solutions for AI workloads: CNI integration (Cilium, Multus), high-performance fabrics (InfiniBand, RoCE), RDMA, and GPUDirect
- Inform and help with storage architecture requirements for AI workloads; collaborate with Storage teams
- Build the foundation for Managed Slurm on Kubernetes for HPC workloads alongside Kubernetes workloads
- Design higher-level platform services for inference, including model serving infrastructure, autoscaling based on inference load, and multi-model deployment patterns
- Design self-healing systems and automation for incident response, root cause analysis, and platform resilience
- Lead chaos engineering efforts to validate system behavior under failure conditions at scale
- Establish operational excellence for a managed service: upgrade automation, security patching, and zero-downtime maintenance
- Serve as the technical bridge between Orchestration and other infrastructure teams (Network, Storage, Security)
- Drive infrastructure-wide decisions enabling successful managed services; understand end-to-end requirements
- Provide input on bare-metal provisioning, network topology, and storage systems for managed services
- Champion consistency and standardization across Lambda's infrastructure stack
- Work directly with customers and internal teams to understand deployments and chart a path to the managed platform
- Set technical direction for Kubernetes services across the Orchestration team and influence roadmap
- Drive reviews and design sessions for scalable, maintainable systems
- Mentor engineers and establish best practices for Kubernetes, distributed systems, and Cloud Native engineering
- Collaborate with Network, Storage, Security, and Customer Success teams; engage with NVIDIA and the open-source community
Qualifications
- 10+ years of experience in software engineering, platform engineering, or SRE, with at least 5 years focused on Kubernetes at scale
- Expert-level understanding of Kubernetes internals: API machinery, controllers, schedulers, operators, CRDs, CSI, CNI, and extension patterns
- Holistic infrastructure expertise spanning compute, networking, storage, and security
- Strong software engineering skills in Go (required) and Python
- Deep experience with GPU orchestration in Kubernetes: NVIDIA GPU Operator, device plugins, DCGM, MIG, time-slicing, GPU-aware scheduling; familiarity with NVIDIA Network Operator and GPUDirect preferred
- Proven technical leadership: driving design decisions, mentoring engineers, influencing infrastructure direction
- Deep experience designing and operating managed services or multi-tenant platforms
- Strong understanding of distributed systems principles (consensus, fault tolerance, etc.)
- Observability at scale: Prometheus, Grafana, distributed tracing, alerting
- Solid Linux systems and networking knowledge (L2-L7), including RDMA, InfiniBand, RoCE
- Experience with infrastructure-as-code and GitOps workflows
Skills
Required:Kubernetes (bare-metal)GoPythonGPU orchestration in KubernetesNetworking for AI workloadsStorage for AI workloads
Benefits
- Health, dental, and vision coverage for you and your dependents
- Wellness and commuter stipends for select roles
- 401k Plan with 2% company match (USA employees)
- Flexible paid time off plan that we all actually use
- Generous cash & equity compensation
Last updated Oct 15, 2026. Interested? Apply on the company site.
About Lambda
The Superintelligence Cloud
The gigawatt-scale AI GPU Cloud built for superintelligence. Featuring on-demand & reserved cloud NVIDIA HGX B200, B300, GB200, GB300 and H200 GPUs for AI training & inference.
AI trainingDeep learningGPU CloudInferenceNVIDIA GPUsliquid-ai-recruiting-targetsetter-30setter-30-2026-q1
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