Product Engineer, Manufacturing

Fluidstack•San Francsisco, CA

5d•$150,000 - $350,000

About The Position

Fluidstack is building civilization-scale infrastructure for AI, focusing on delivering gigawatts of compute faster than anyone else. This involves rethinking every layer of the stack, from acquiring power to designing, building, and operating data centers. The Decision Team is responsible for automating the delivery of gigawatts by turning processes from manual tasks into software, deploying product teams alongside experts on factory floors, and ensuring every lesson learned at one site benefits all projects. The role of Product Engineer, Manufacturing is crucial in this mission, focusing on building quality control as software, creating self-replanning factory schedules, continuously scoring third-party integrators, and closing the corrective-action loop for defects. The Product Engineer will embed with modular design engineers, quality managers, and factory operators to transform BOM lineage, test history, revision, and acceptance evidence into a graph-based system that answers critical shipping questions. The company emphasizes speed, scale, and a deep care for the problem space, hiring individuals who are driven to solve complex challenges and contribute to the future of AI infrastructure.

Requirements

Shipped production code in Go, Python, or TypeScript, and can pick up whatever language the problem demands.
Built real features on LLM APIs (OpenAI, Anthropic, or open-weight models), MCP servers, and agentic frameworks.
Works daily with AI coding tools like Claude Code and Cursor, and gets agents doing useful work autonomously alongside them.
Identifies problems, designs the solution, and ships it without waiting for direction or approval.
Moved fast under deadline while leaving foundations that other engineers extended after you moved on.
Sat with domain experts who don't write software, turned their judgment into working systems, and gotten them to adopt what you built on a production line.
Product taste shows in what you've shipped: interfaces the people on the floor call obvious, and workflows that match how the work actually happens.

Nice To Haves

MES or PLM systems.
Inspection and test plans and factory acceptance testing.
NCR and corrective-action workflows.
BOM management.
Scheduling and optimization problems.

Responsibilities

Build quality control as software: inspection and test plans, first-article inspections, and factory acceptance test procedures generated per asset from the design revision, with submitted results verified against spec automatically, hold points enforced, and a failed check opening a nonconformance report with the evidence attached.
Ship a factory schedule that replans itself: work orders, sequencing, and kitting derived from demand and the bill of materials, with throughput and yield live per line and integrator, recomputing and flagging delivery impact when a test fails or a shipment slips.
Score third-party integrators continuously on measured defect density, first-pass test rate, and corrective-action speed, so qualification, load balancing, and the next award happen on performance the graph already holds.
Close the corrective-action loop: trace a defect found at commissioning or in the field back to the causing design revision, factory, and bench, and land the fix in the next run's inspection plan automatically.
Embed with modular design engineers, quality managers, and factory operators in factories and at integrator facilities, and turn every skid, module, and serialized component's BOM lineage, test history, revision, and acceptance evidence into a graph where the answer to "can we ship it" is a query.