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Compute Intelligence Engineer

Prime Intellect· Compute / Finance
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San Francisco$225k - $300kFull-timePosted 4mo ago

About the role

Compute Intelligence Engineer building the data infrastructure and intelligence platform to provide a live, accurate picture of Prime Intellect's compute—supply, demand, utilization, and capacity planning—across the company.

Responsibilities

  • Stand up Prime Intellect's data warehouse (Snowflake, BigQuery, or equivalent) and the pipelines that feed it — compute telemetry, billing and usage data, partner and supply data, CRM, and financial systems
  • Build the data models and transformations (dbt or equivalent) that turn raw data into a clean, queryable, trustworthy source of truth
  • Build dashboards and reporting that give the company a live picture of compute supply, demand, utilization, upcoming capacity, and bottlenecks
  • Build a queryable, AI-accessible layer on top of the warehouse so teams across the company can answer their own questions without going through a data analyst
  • Build the data systems that track our compute supply end-to-end: what we have, what's committed, what's coming online, and what's utilized vs. idle
  • Develop the views and models that surface where our bottlenecks are — and make upcoming supply legible to the teams that depend on it
  • Connect supply data to demand signals so the company can see, in one place, how capacity maps to what we're selling and building
  • Serve as the data backbone connecting Compute Partnerships, Growth, and Research — building the systems that let them operate from shared, accurate information
  • Partner with Growth on understanding upcoming supply and how it maps to what they can sell
  • Partner with Compute Partnerships on utilization, commitments, and supply tracking
  • Partner with Research on scaling needs and capacity planning
  • Build pipelines and systems that run unattended, stay in sync, and fail gracefully
  • Establish the data quality, documentation, and infrastructure standards that let the data layer scale with the company
  • Partner with Engineering on shared infrastructure, security, and data standards

Qualifications

  • 3–7+ years in data engineering, analytics engineering, GTM/growth engineering, or similar roles where you've built data infrastructure that served real business outcomes
  • Strong technical skills: comfortable building and maintaining data warehouses, writing production-quality pipelines (Python, SQL), modeling data (dbt or equivalent), and connecting disparate systems via APIs
  • Experience with modern data stack tooling — Snowflake / BigQuery / Databricks, dbt, orchestration (Airflow, Dagster, etc.), and BI/dashboarding tools
  • A builder's instinct paired with business judgment — you don't just build what's asked; you understand the business well enough to build the right thing
  • Comfortable being the data backbone for cross-functional teams — translating between business needs and the systems that serve them
  • Familiarity with modern AI tooling and an interest in building AI-accessible data layers (natural-language querying, LLM-powered analytics) that let non-technical teams self-serve
  • High ownership — you see gaps and build the fix before anyone asks
  • Comfortable in ambiguity and speed; you'll be defining what the data layer looks like from scratch
  • AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster

Skills

Required:Data warehouse developmentETL/ELT pipelinesData modelingAPI integrationOrchestration toolingBI/dashboarding
Nice to have:AI-enabled data interfaces

Benefits

  • Cash Compensation Range of $225-300k + meaningful equity
  • Flexible work (remote or San Francisco)
  • Visa sponsorship and relocation support
  • Professional development budget
  • Team off-sites and conferences
  • A front-row seat to building the infrastructure layer for open AI
Last updated Jul 15, 2026. Interested? Apply on the company site.

About Prime Intellect

Commoditizing Compute & Intelligence

Prime Intellect democratizes AI development at scale. Our platform makes it easy to find global compute resources and train state-of-the-art models through distributed training across clusters. Collectively own the resulting open AI innovations, from language models to scientific breakthroughs.

AI developmentbessemer-ai-infrastructure-2026compute resourcesdistributed trainingmodelsreinforcement-learning-platformsscience
Company profileWebsite

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