Engineering 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.

Fleet Engineering owns the full lifecycle of Lambda's production systems infrastructure — new product introduction, deployment, operation, and reliability of our GPU fleet. We enable the building and running of that infrastructure with speed, ease, and quality. The Fleet Engineering teams:

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  Lead and grow a distributed team of top-talent engineers responsible for the deployment and operation of production systems infrastructure.

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  Work cross-functionally to deliver projects and deployments on time, ensuring alignment across stakeholders.

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  Identify opportunities for efficiency gains in the tools, processes, and automation that teams across the organization rely on day to day.

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  Give stakeholders clear visibility into project progress, risks, and outcomes.

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  Participate in qualification efforts for new technologies entering our production deployments.

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  Drive outcomes by managing staff allocation, project priorities, deadlines, and deliverables.

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  Hold regular 1:1s, give constructive feedback, and support career development for your team.

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  Contribute to reliability through participation in our Incident Management and Review programs.

• Have 3+ years leading or managing engineers, in AI/ML infrastructure or another large-scale compute environment.

• Have owned production systems with real SLAs, and can balance keeping things running against long-term, high-impact work — paying down toil and technical debt along the way.

• Work confidently in Linux and can debug across the OS, hardware, and networking layers.

• Can lead technical design on medium-to-large efforts: take an ambiguous problem, write the doc, drive alignment across teams, and ship.

• Work well under deadlines and structured project plans, and can tactfully negotiate changes to timelines when reality demands it.

• Collaborate effectively with peer engineering managers on efforts that cut across deployment and operations.

• Build high-performing teams deliberately — through hiring, upskilling, planned skills redundancy, performance management, and clear expectations.

• Have excellent problem-solving and troubleshooting instincts.

• Are excited about working at the intersection of hardware, software, and physical datacenter builds.

• Leave systems, and the teammates around you, better than you found them.

Depth in any one of these is a strong signal, and helps us place you on the right team. Nobody has all of them.

• Linux systems administration, TCP/IP networking, automation, and scripting.

• Bare metal provisioning and lifecycle management — PXE, Redfish, IPMI, BMC, DHCP, DNS.

• Strong coding ability in at least one language, plus comfort with APIs, distributed systems, and automation pipelines.

• The technologies underpinning our cloud business: GPU acceleration, virtualization, cloud computing.

• Datacenter physical infrastructure: racks, switches, InfiniBand fabric, power domains.

• Network source-of-truth or DCIM tooling (NetBox or similar), and data quality practice at scale.

• Building Linux distributions, or managing OS customization and imaging.

• Incorporating AI-assisted development tools into engineering workflows — code generation, debugging, test development, documentation.

• Customer awareness, empathy, and diplomacy.

• Bachelor's degree or equivalent experience in a technical field.

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.

• 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

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.