Senior Technical Program Manager - Public Cloud

About the role

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 Jose, San Francisco, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

What You’ll Do

• Own complex programs from planning through rollout, delivering Lambda Public Cloud roadmap commitments with clear accountability for schedule and quality.
• Turn product priorities and engineering strategy into execution plans with defined outcomes, milestones, owners, and decision points.
• Partner with engineers on architecture, implementation estimates, and sequencing; make dependencies, risks, and delivery tradeoffs visible early.
• Coordinate launches across compute, networking, storage, and the cloud control plane, aligning Engineering, Product, Infrastructure, SRE, Security, and Support on readiness and customer impact.
• Build a practical delivery cadence that connects roadmap planning, capacity availability, testing, release gates, rollout plans, and operational handoffs.
• Give teams and leadership a shared view of progress, decisions, and blockers. Drive timely escalation, resolve cross-team dependencies, and follow through on commitments.
• Define launch success measures for service availability, provisioning, performance, and customer experience; use post-launch reviews to improve future delivery.

You

• Bring at least 8 years in technical program leadership or engineering management, with a record of shipping complex cloud services.
• Understand software delivery, infrastructure architecture, and distributed systems well enough to assess implementation choices and challenge assumptions with engineers.
• Have worked with GPU infrastructure, machine learning platforms, or orchestration systems such as Kubernetes.
• Can independently lead several teams through ambiguous requirements, competing priorities, and delivery risks, influencing decisions without direct authority.
• Communicate technical issues and business consequences clearly, adapting the detail for engineering teams and senior stakeholders.
• Use delivery methods and planning tools effectively, choosing processes that improve execution and ownership.

Nice to Have

• Experience launching customer-facing infrastructure services, including APIs, tenant isolation, access controls, metering, or billing.
• Familiarity with GPU capacity planning, fleet lifecycle, cloud service reliability, and production incident follow-up.
• Experience helping a growing organization establish repeatable planning and delivery practices.

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.