Compute Intelligence Engineer
$225k - $300k • Remote • San Francisco • FullTime
Posted 3mo ago
About the job
Prime Intellect is building the open superintelligence stack, a platform designed to provide AI labs with the infrastructure they need for advanced AI development. Their platform, Lab, integrates compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for post-training at frontier scale. This role focuses on the critical compute aspect, aiming to create a data infrastructure and intelligence platform that provides a real-time, accurate view of the company's compute resources, including supply, demand, and bottlenecks. This is a hands-on data engineering role where you will establish the data warehouse, develop pipelines to ingest data from various sources, model this data into a reliable source of truth, and create dashboards and a queryable layer for company-wide use. The foundations laid in this role will serve as the data backbone for the company's scaling efforts.
Responsibilities
- Build the Compute Intelligence Platform, including data warehouse setup and pipeline development.
- Develop data models and transformations to create a clean and trustworthy source of truth.
- Create dashboards and reports for a live view of compute supply, demand, utilization, and bottlenecks.
- Build an AI-accessible query layer for self-service data analysis.
- Develop systems to track compute supply end-to-end, including commitments and upcoming capacity.
- Surface data on compute bottlenecks and make upcoming supply visible to dependent teams.
- Connect supply data to demand signals to show capacity mapping to sales and development.
- Serve as the data backbone connecting Compute Partnerships, Growth, and Research teams.
- Partner with Growth on understanding supply and sales mapping.
- Partner with Compute Partnerships on utilization, commitments, and supply tracking.
- Partner with Research on scaling needs and capacity planning.
- Build reliable, unattended pipelines and systems.
- Establish data quality, documentation, and infrastructure standards for scalability.
- Partner with Engineering on shared infrastructure, security, and data standards.
Requirements
- 3-7+ years in data engineering, analytics engineering, GTM/growth engineering, or similar roles.
- Experience building data infrastructure for real business outcomes.
- Strong technical skills in data warehousing, production-quality pipelines (Python, SQL), and data modeling (dbt or equivalent).
- Experience connecting disparate systems via APIs.
- Familiarity with modern data stack tooling (Snowflake/BigQuery/Databricks, dbt, orchestration tools, BI/dashboarding tools).
- A builder's instinct paired with business judgment.
- Comfortable serving as a data backbone for cross-functional teams.
- Familiarity with modern AI tooling and an interest in building AI-accessible data layers.
- High ownership and proactive problem-solving.