# Product Manager, Compute Operations

**Company:** [Fluidstack](https://hotfix.jobs/companies/fluidstack)
**Location:** New York, NY, San Francisco, CA, Austin, TX, Seattle, WA
**Role:** Product Management
**Salary:** $245k – $288k/yr
**Experience:** 3+ years
**Skills:** technical product management, Data Modeling, ontology development, System Design, stakeholder discovery, metrics definition, llm-powered applications
**Posted:** 2026-08-11

> Product Manager owning ontology, data models, and product surfaces for gigawatt-scale AI compute production. Drive discovery, technical tradeoffs, metrics, and end-to-end delivery to turn fragmented operational data into a single source of truth for engineers and operators.

## Job Description

## Role Scope
- Own product direction for the team's ontology and data products serving compute production: the roadmap, the priorities, and the success metrics that justify them
- Turn messy compute production domains into data models, specs, and product surfaces clear enough that engineers can ship against them without a second round of discovery
- Drive technical tradeoffs with engineers and ship end to end, from problem definition through delivery
- Run direct discovery with compute production stakeholders to understand their domain, then validate that what you built actually changes how they work
- Define and track the metrics that prove the product is delivering real leverage, and cut or redirect work that isn't

## Requirements
- 3+ years of technical product management, ideally on data, platform, or ontology products
- A track record of shipping products with measurable impact, and the numbers to show it
- You can reason about system design and hold your own with engineers on technical tradeoffs, not just relay their conclusions
- Strong written communication: crisp specs, and prioritization rationale sharp enough that stakeholders who disagree still understand why you chose what you chose
- You're comfortable in ambiguity and know how to impose structure where none exists, turning an unmapped operational domain into a model others can build on

## Nice-to-Haves
- Exposure to compute or datacenter operations, infrastructure systems, or building LLM-powered applications

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