lambda · San Francisco Office (Fremont St)
Skills: React, Python, SQL, AWS, Docker
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. What You'll Do - Build and own the systems that digitally capture Lambda’s physical datacenter hardware, ensuring physical host and rack state stays accurate in our inventory source of truth - Design and implement conflict resolution and precedence logic across competing data sources (vendor manifests, on-site observation, and system-observed telemetry) - Build validation tooling that catches inventory errors before they propagate downstream - Design attestation and constraint systems that validate physical topology, cabling, rack composition, and containment, against intended logical configuration at scale - Lead the technical design of rack- and asset-level scanning workflows, including provisional-vs-verified data states, tagging/versioning of data provenance, and safe rollout of reduced-friction scanning modes - Partner cross-functionally with DC Operations, Engineering, and vendors to define what physical data needs to be captured, when, and by whom, and drive alignment on where automation should replace manual reconciliation - Monitor production health of capture and validation pipelines, hold SLAs, and drive resolution when physical/logical state drifts You - Have 5+ years of engineering experience - Are fluent in Python, Go, or similar - Comfortable with APIs, distributed systems, and automation pipelines - Have owned production systems with real SLAs - Can lead technical design on medium-to-large features: t…
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