Engineering Program Manager - Fleet Engineering
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.
About the Team
The Fleet Engineering team is responsible for the logical deployment of cutting edge NVIDIA GPU clusters, the reliability of the production fleet, and the tools and processes to support these outcomes.
About the Role
Reporting to the Director of Fleet Engineering, your role as an Engineering Program Manager is to coordinate collaboratively across a set of cross functional teams to ensure we deliver new GPU capacity on time and at 100% quality. You will be responsible for managing and coordinating the efforts of multiple teams, communicating progress and actively managing risks and prioritization. You will work collaboratively with Product and Infrastructure engineering teams to improve transparency, metrics, automation and overall efficiency for the team.
We value diverse backgrounds, experiences, and skills, and we are excited to hear from candidates who can bring unique perspectives to our team. If you do not exactly meet this description but believe you may be a good fit, please still apply and help us understand your readiness for this Manager role. Your application is not a waste of our time.
What You’ll Do
Partner with Fleet Engineering Managers to ensure the teams are aligned on expectations, track progress towards deliverables, providing repeatable & scalable programs.
Identify opportunities for improvement: ensuring we are capturing the appropriate signals throughout the program and facilitating continuous improvement.
Work with Fleet Engineering Deployments on executing against tight deadlines while improving process, tooling, automation.
Collaborate closely with a broad set of stakeholders, including Platform & Infrastructure engineering, Program Management, Product Management, DC Operations, and finance
Lead cross-functional engineering teams to deliver complex infrastructure projects from concept to deployment. Define scope, goals, and deliverables; plan resources, timelines, risks and ensure execution aligns with organizational objectives.
Demonstrate technical expertise in infrastructure technologies, including NVIDIA GPUs, hardware troubleshooting, lab methodologies, and automation tools.
Drive risk management and stakeholder communication by proactively identifying issues, driving realtime and inflight tight timeline projects, and providing transparent updates on progress and milestones.
Continuously refine project management processes to improve efficiency, collaboration, and cross-functional alignment with product, operations, and security teams. Maintain a customer-focused approach in defining and meeting technical requirements.
You
10+ years of infrastructure experience with 5+ years performing program management for major projects including capital projects or hyperscaler infrastructure deployment
Demonstrated experience leading a team of engineers on complex, cross-functional projects in a fast-paced environment.
Comfortable managing cross functional teams and driving decisions and communications
Experience successfully designing and implementing simple, scalable processes that solve complex problems.
Thrive in ambiguous, fast-paced environments, You bring clarity and order to the rest of the team.
Bachelor's degree in Computer Science, Engineering, or a related technical field.
Proven track record of successfully leading and delivering complex technical projects.
Exceptional leadership, communication, and interpersonal skills.
Ability to thrive in a fast-paced, high-pressure environment and manage multiple projects simultaneously.
Nice to Have
Experience managing hybrid hardware deployment and software engineering projects.
Experience in a hyperscaler (CSP), neocloud provider (NCP), or high-performance computing (HPC) production environments.
Worked closely with product managers to deliver products to specification.
Deep understanding of infrastructure technologies and software development best 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.
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
A Final Note:
You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.
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.