The Decision TeamExamples of key problems the team is working on- Automate the delivery of gigawatts. Every process that takes AI infrastructure from land to live compute becomes software: schedules, decisions, and todos generated from a live knowledge graph instead of chased by hand.
- Forward-deploy beside the experts. Product teams sit with quality managers, sourcing leads, and deployment engineers on factory floors and sites, and turn their judgment into systems that reach every unit.
- Deliver every supercomputer faster than the last. Dozens of concurrent projects feed one graph, so every lesson learned at one site becomes a preventive check at all of them.
Role Scope- Own the automation roadmap for compute production as its first product manager: you decide which parts of keeping GPU fleets worth billions healthy become software next, across fleet health, repair and RMA, hardware qualification, on-call, facility maintenance, and the asset model, and you defend the order with numbers: machines per operator, time to return to service, pages per failure mode.
- Land the systems already in flight: a maintenance system for lockout tagout and work orders is live at one site and rolls out to two more, every asset register loads before the first external audit this fall, and the legacy datacenter inventory retires before the next building energizes. Your first quarter is sequencing those three and calling the cutover dates.
- Live on the floor and the rotation: embed with the production engineers and facility operators who run the fleet, sit the on-call shift, map where shift hours actually go, and turn that map into the roadmap everyone can cite, including the SOP source of truth and training records a hyperscaler customer asked to audit.
- Define done for every workflow: the number each automation must clear before it counts, published where the team sees its own toil falling, plus the site SLO and deployment cycle time dashboards the customer reads, so "did it work" is answered by the system, not a status meeting.
- Run the queue for the four Decision Engineers hired into this function: there is no team lead between you and them. You own what ships next and why, they own how, you prototype your own ideas with AI tools (Claude Code, Cursor, LLM APIs, MCP) and put working software into a shift lead's hands instead of writing requirements, and you both answer for the outcome, employee-hours per gigawatt.
What We're Looking ForThe below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly,tell us where you would.- You've shipped technical products for operations or infrastructure users, often after starting as an engineer or operator.
- You've owned a product measured on operational numbers: uptime, MTTR, machines per technician, audit findings closed, and not on launches.
- You've been the first product person in a function and set the roadmap, the metrics, and the working cadence from nothing.
- You prototype with AI tools daily and ship what works instead of waiting on an engineering queue.
- You're credible with production engineers and SREs on the rotation and with leadership in the same hour, and you've gotten both to change how they work.
- You've owned prioritization for a team of engineers: you decided what shipped next and defended why.
- Your product and design taste shows in what you've shipped: interfaces the people on the rotation call obvious, workflows that survive a 2am page.
- Bonus: Datacenter or GPU fleet operations. CMMS, DCIM, or asset management rollouts. SRE and observability tooling. Hardware qualification or burn-in. Compliance or audit readiness. Time on an on-call rotation.
We are committed to pay equity and transparency.
