Job description

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This position requires presence in our San Francisco, San Jose, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. The Role Lambda’s Core Cloud Platform organization builds the software and services that turn large-scale GPU infrastructure into reliable, customer-facing cloud products. The team owns foundational platform capabilities across Managed Kubernetes, resource lifecycle, workload orchestration, cloud APIs, automation, observability, and multi-region operations. The immediate focus for this role includes evolving Lambda’s Managed Kubernetes platform: making it easier and safer to provision, upgrade, operate, and scale Kubernetes clusters for demanding AI workloads. The platform integrates closely with Lambda’s underlying compute, networking, storage, fleet, and security systems. As Engineering Manager, you will lead a team building and operating these foundational platform services. You will own the team’s people, execution, technical quality, and production outcomes while partnering with senior engineers to set technical direction. This is a high-leverage role at the intersection of cloud infrastructure, distributed systems, Kubernetes, and the customer experience. What You’ll Do - Lead the design, implementation, and production operation of foundational cloud-platform services. - Own the technical roadmap for making the platform more distributed, resilient, observable, and operationally efficient. - Ensure the platform operates reliably across a growing multi-datacenter and multi-region fleet, including appropriate handling of partial failures and long-running workflows. - Partner with senior and staff engineers to make sound architectural decisions across distributed services, stateful systems, APIs, schedulers, controllers, and automation. - Define clear contracts and integration patterns between the cloud platform and the compute, networking, fleet, security, and customer-facing systems around it. - Lead and grow a team of senior and staff engineers; hire exceptionally, develop people, maintain a high-performance bar, and address underperformance directly. - Own project planning, prioritization, and delivery aligned with Lambda’s business objectives and customer commitments. - Establish strong engineering practices across design reviews, testing, CI/CD, observability, incident response, and on-call operations. - Collaborate with peer Engineering Managers and cross-functional partners to resolve dependencies and deliver complete customer outcomes. - Improve engineering leverage through automation, effective operating mechanisms, and responsible use of AI-assisted engineering. - Stay current with developments in Kubernetes, cloud-native infrastructure, GPU orchestration, and platform automation, and apply them where they materially improve Lambda’s platform. You - 4+ years of engineering management experience with a demonstrated track record of growing high-performing teams - 7+ years of software engineering IC experience, including principal or staff-level ownership of mission-critical distributed systems - 8+ years implementing business-critical services in Python or Go, from conception through production - Experience building systems that coordinate across multiple independently-owned infrastructure services (compute, networking, storage) without owning them directly - Background in multi-region deployment strategies, cross-datacenter state management, and high-availability architectures - Strong track record of owning projects end-to-end: architecture, delivery, operations, and continuous improvement - Excellent cross-functional collaboration - proven ability to drive alignment across infrastructure, platform, and product teams Nice to Have - Awareness of the evolving bare metal and GPU infrastructure ecosystem - including tools like NVIDIA NiCo (NCX Infra Controller) for DPU-enforced lifecycle automation, BlueField DPU capabilities, and where industry standards for multi-tenant bare metal management are heading - Experience evaluating or adopting vendor infrastructure tooling into an existing platform - performing a full migration, having the judgment to assess fit, risk, and timing - Familiarity with Kubernetes or Slurm - useful context for how this team integrates with Lambda’s cluster orchestration layer, but not required for the role itself - Experience in the AI, ML, or GPU hardware industry - Proven track record designing large-scale cloud IaaS platforms from the ground up - Exposure to IPO readiness, enterprise compliance, or security requirements at scale Values We’re Looking For - Hands-on when needed: You can get into the details when the team or system needs it without becoming the long-term bottleneck. - High accountability: You take responsibility for delivery and production outcomes and do not tolerate systems remaining unreliable. - Business and customer alignment: You connect technical priorities to the outcomes that matter for Lambda and its customers. - Sound judgment: You make decisions with incomplete information, manage risk, and change direction when the evidence changes. - Systems builder: You create teams, processes, and technical foundations that operate effectively without depending on constant intervention. - Agency with context: You find responsible paths through obstacles without creating unnecessary risk or operating as a cowboy. - Low ego and strong collaboration: You handle disagreement directly, learn when you are wrong, and build productive cross-functional relationships. - Learning through failure: You turn operational and organizational failures into stronger systems and lasting improvements. Salary Range Information The 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: lambda.ai - 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 Equal Opportunity Employer Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

Requirements

Must-haves

If you'd like to build the world's best AI cloud, join us.
Note: This position requires presence in our San Francisco, San Jose, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.
What You’ll Do
Lead the design, implementation, and production operation of foundational cloud-platform services.
Own the technical roadmap for making the platform more distributed, resilient, observable, and operationally efficient.
Ensure the platform operates reliably across a growing multi-datacenter and multi-region fleet, including appropriate handling of partial failures and long-running workflows.
Partner with senior and staff engineers to make sound architectural decisions across distributed services, stateful systems, APIs, schedulers, controllers, and automation.
Define clear contracts and integration patterns between the cloud platform and the compute, networking, fleet, security, and customer-facing systems around it.
Lead and grow a team of senior and staff engineers; hire exceptionally, develop people, maintain a high-performance bar, and address underperformance directly.
Own project planning, prioritization, and delivery aligned with Lambda’s business objectives and customer commitments.
Establish strong engineering practices across design reviews, testing, CI/CD, observability, incident response, and on-call operations.
Collaborate with peer Engineering Managers and cross-functional partners to resolve dependencies and deliver complete customer outcomes.

Nice-to-haves

Experience evaluating or adopting vendor infrastructure tooling into an existing platform - performing a full migration, having the judgment to assess fit, risk, and timing
Experience in the AI, ML, or GPU hardware industry
Proven track record designing large-scale cloud IaaS platforms from the ground up
Exposure to IPO readiness, enterprise compliance, or security requirements at scale
Values We’re Looking For
Hands-on when needed: You can get into the details when the team or system needs it without becoming the long-term bottleneck.
High accountability: You take responsibility for delivery and production outcomes and do not tolerate systems remaining unreliable.
Business and customer alignment: You connect technical priorities to the outcomes that matter for Lambda and its customers.
Sound judgment: You make decisions with incomplete information, manage risk, and change direction when the evidence changes.
Systems builder: You create teams, processes, and technical foundations that operate effectively without depending on constant intervention.
Agency with context: You find responsible paths through obstacles without creating unnecessary risk or operating as a cowboy.
Low ego and strong collaboration: You handle disagreement directly, learn when you are wrong, and build productive cross-functional relationships.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aikubernetesci/cdpythongomlmachine learning

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Paid Time Off

Wellness