About the RoleLambda Kubernetes Service (LKS) is an API-first Kubernetes platform for AI training and inference on Lambda infrastructure. We're looking for an Engineering Manager to lead the team building its customer-facing platform capabilities: cluster runtime, system components, managed add-ons, and AI workload orchestration.
You'll lead the engineering team and partner with the Hosted Control Plane team and Lambda's Compute, Networking, Storage, IAM, Security, and Product teams. The goal is a reliable, extensible Kubernetes experience from a functional vanilla cluster to vetted capabilities such as GPU and network operators, and orchestration options such as Slurm through Slinky.
What You'll Do- Build and lead the engineering team; hire strong engineers, develop technical leaders, and set a high bar for ownership and quality.
- Define the technical strategy and roadmap for LKS platform capabilities and Kubernetes runtime.
- Deliver a reliable baseline cluster experience using upstream, CNCF-conformant Kubernetes.
- Own the integration and lifecycle of managed add-ons, including qualification, compatibility, releases, and customer choice.
- Build Kubernetes capabilities for AI workloads, starting with Slurm through Slinky and evaluating options such as Volcano and LLMD as needs grow.
- Partner with the Hosted Control Plane team on cluster lifecycle, upgrades, release readiness, and incident response.
- Work across Lambda infrastructure and product teams to deliver secure, supportable integrations.
- Communicate progress, risks, and customer impact clearly to leadership and partner teams.
You- Have 9+ years of software engineering experience, including 3+ years leading engineering teams.
- Have built or operated Kubernetes platforms, managed Kubernetes services, or container infrastructure.
- Bring strong technical judgment across Kubernetes, platform APIs, operators, and cluster lifecycle.
- Can guide tradeoffs across extensibility, compatibility, security, reliability, and customer experience.
- Build strong teams and work effectively across engineering, product, and infrastructure organizations.
- Communicate clearly and turn ambiguous needs into pragmatic plans and results.
- Hold a BS, MS, or PhD in Computer Science or a related field, or have equivalent practical experience.
Nice to Have- Experience with GPU operators, AI infrastructure, or GPU-aware Kubernetes.
- Experience with Slurm, Slinky, Volcano, LLMD, Kueue, Ray, or similar orchestration systems.
- Experience with Kubernetes networking, storage, upgrades, or managed add-on catalogs.
Salary Range InformationThe annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
About Lambda- Founded in 2012, with 500+ employees, and growing fast
- Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
- We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
- Our values are publicly available: https://lambda.ai/careers
- We offer generous cash & equity compensation
- 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
