Software Engineer - Fleet Orchestration

Lambda•San Francisco, CA

2d•$266,000 - $395,000•Hybrid

About The Position

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.

Requirements

5+ years of engineering experience (degree not required)
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 Haves

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

Responsibilities

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