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Fluidstack is building civilization-scale AI compute infrastructure, acquiring power, designing and operating data centers at gigawatt scale. The company operates with extreme urgency and first-principles thinking to deploy frontier compute faster than anyone else.
As a Product Engineer on the Manufacturing & Supply Chain team (called "The Decision Team"), you will own end-to-end systems that automate the delivery of gigawatts of compute infrastructure. You'll work embedded with sourcing leads, quality managers, factory operators, and warehouse teams to turn their operational judgment into software systems.
Key problem areas you'll tackle:
- Transform bill of materials into the order book: build systems where every template bill carries price and lead time, every project bill locks to a building, and every purchase order derives from a single source of truth instead of spreadsheets. This controls tens of billions of dollars in GPU, optics, switchgear, and cooling procurement.
- Make procurement tracking trustworthy: ship code that runs against live vendor emails, documents, and general contractor purchase orders through extractors you build. Rules for status, criticality, and latency detection run in code so drift is caught within a week and recovery plans are drafted before vendors call.
- Close the loop from receiving to payment: every delivery matches a PO line, warehouse bins track serial numbers, cycle counts score against accuracy gates, and finance three-way matches from the same record. One answer to "did we get what we paid for" instead of three.
- Ship manufacturing as software before the factory opens: manufacturing BOMs, engineering change notices, and drawing trees live in one model. Inspection, test plans, and first-article procedures generate per asset from design revision. Failed checks open nonconformances with evidence attached and rescores vendors.
- Embed with operations teams on factory floors and in vendor calls, turning their judgment into systems that decide order schedules, cash demand by month, and payment schedules.
You will identify problems, design solutions, and ship them without waiting for direction. You move fast under deadline while leaving data models and foundations that other engineers extend. You have credibility with operators and drive adoption of software inside their real deadlines (live production runs, quarter-end closes). Your product taste shows in interfaces operators call obvious and workflows that match how work actually happens.
The company operates with full autonomy ("be a barrel"), insane urgency, first-principles reasoning, and focus on building something that matters to the world.
REQUIREMENTS:
- Shipped production code in Go, Python, or TypeScript; pick up whatever language the problem demands
- Built real features on LLM APIs (OpenAI, Anthropic, or open-weight models), MCP servers, and agentic frameworks
- Put document extraction into production against messy real inputs
- Work daily with AI coding tools like Claude Code and Cursor; get agents doing useful work autonomously
- Identify problems, design solutions, and ship without waiting for direction or approval
- Moved fast under deadline while leaving extensible data models and foundations
- Earned credibility with operators in factories, warehouses, or procurement; driven adoption of software inside real deadlines
- Product taste demonstrated in shipped work: obvious interfaces and workflows matching actual work
BONUS EXPERIENCE:
- MES, ERP, WMS, or TMS systems
- BOM lineage, engineering change control, serialized component traceability
- Supplier quality (NCRs, CAPA, FAI)
- Three-way match and receiving reconciliation
- LLM extraction over vendor documents
- High-volume hardware supply chains
