Product Manager, Business Operations - fluidstack

We exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants.

There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it.

We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.

We hire people who care deeply about this problem space. If that is you, please apply!

HOW WE OPERATE

• Extreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done.
• Velocity. We drive everything forward as fast as possible.
• First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.
• Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.

THE BUSINESS OPERATIONS TEAM

The Business Operations team builds the ontology and data products that turn Fluidstack's operational reality into structured, usable systems, so the people running the largest AI compute buildout in history can make decisions from data instead of spreadsheets.

Examples of key problems the team is working on:

• Turn messy operational domains (contracts, vendors, workflows, financial operations) into a shared ontology that engineers can build against and operators actually trust
• Build data products and product surfaces that replace ad hoc tracking with structured, queryable systems of record
• Apply LLM-era tooling to operational workflows where structured data plus automation can remove hours of manual work per week
• Prove leverage with metrics, so every product the team ships can show the operational time or errors it eliminated

ROLE SCOPE

• Own product direction for the team's ontology and data products: the roadmap, the priorities, and the success metrics, with rationale clear enough that engineers and stakeholders can challenge it on the merits
• Turn messy business operations domains into data models, specs, and product surfaces precise enough for engineers to ship against without a second round of discovery
• Drive technical tradeoffs with engineers and ship end to end, from problem definition through launch and iteration