Staff Software Engineer, GPU Infrastructure Lifecycle Management

Responsibilities

• Build the provisioning state machine: design and implement the software that models the full lifecycle of a physical host from discovery, inference bring-up to GPU driver/CUDA stack, health validation, and decommission/RMA — as explicit, versioned states and transitions.
• Build the self-service API: design declarative APIs and a control plane so the inference team can request, scale, and tear down inference clusters with one API call — no ticket, no human in the loop.
• Automate self-healing: detect degraded or failed nodes, drain them safely, trigger repair or replacement, and reintroduce healthy capacity into the pool automatically.
• Own reliability of the pipeline: idempotency, retries, rollback, and drift detection so the provisioning system is as dependable as any other production service.
• Partner with the inference/ML platform team: understand the cluster shapes they need — topology, interconnect, scheduling constraints — and encode them as first-class abstractions in the platform.
• Engineer it like software: strong typing, automated tests, code review, versioning, and CI/CD for infrastructure code — this is a product, not a collection of Ansible playbooks.

Requirements

• Strong software engineering background in Go, Python, Rust, or similar.
• Experience with durable workflow orchestration tools such as Temporal, Cadence, or equivalent to run long-lived, manifest-driven workflows that survive failures and resume mid-execution.
• Experience building software control planes or orchestration systems that model state and reconcile it over time (e.g., Kubernetes controllers/operators, custom reconciliation loops, workflow engines).
• Experience with event-driven systems — designing and building software around message queues, event streams, or pub/sub (e.g., Kafka, NATS, SQS).
• A product mindset. You’ve built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship.

Nice-to-Haves

• Exposure to bare-metal provisioning (PXE/iPXE, Redfish/IPMI, BMC) and/or networking fundamentals (VLANs, BGP, fabric design), or GPU/accelerator infrastructure.
• Experience with GPU cluster software stacks (NCCL, CUDA, InfiniBand/RoCE).
• Prior work at a hyperscaler, GPU cloud, or datacenter-scale infrastructure organization.
• Systems programming in Rust or Go.

Compensation

• US base salary range: $240,000 - $280,000 + equity + benefits.