Software Engineer - Fleet Orchestration

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

What You'll Do

• Build and own fleet data systems that make Lambda's GPU datacenter hardware legible at scale — indexing, validating, and reconciling physical host state against intended logical configuration

• Lead the design and implementation of automation that orchestrates GPU cluster deployments from logical design import and racking through OS provisioning, validation, and customer hand-off

• Design systems that continuously validate consistency between intended and actual state across large-scale GPU environments, catching drift before it causes deployment failures or delays

• Design and implement ownership, global locking, readiness gating, and action safety systems that keep fleet operations coordinated across teams and tools

• Own Fleet Orc's technical contribution to new datacenter site bring-up, working cross-functionally with HPC Deployments, DC Ops, Network Engineering, and Core Infrastructure

• Monitor production health, hold SLAs, and drive resolution when things drift

You

• Have 5+ years of engineering experience (degree not required)

• Are fluent in Python, Go, or similar — comfortable with APIs, distributed systems, and automation pipelines

• Can reason about PXE boot, firmware provisioning, IPMI/BMC interfaces, and network services like DNS and DHCP from first principles

• Have owned production systems with real SLAs

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

• Have worked cross-functionally and influenced technical decisions beyond your immediate team

• Have mentored peers and left systems — and teammates — better than you found them

Nice to Have

• Experience in the machine learning or AI infrastructure industry

• Familiarity with datacenter physical infrastructure — racks, switches, InfiniBand fabric, power domains

• Background that blends software engineering with systems or infrastructure engineering

• Experience with network source-of-truth systems (NetBox or similar) or DCIM tooling

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

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.