Pioneering Intelligence: Agentic AI Co-Op
About The Position
The Agentic AI team builds autonomous agents that plan, build and iterate long-running research and engineering tasks with limited supervision. We work on agent design, orchestration, durable execution across tools and data sources, and practical evaluation. This role involves building and improving agents that use APIs, tools and large datasets, rethinking traditional research and software-development workflows using an agentic SDLC, designing evaluations for accuracy, reliability and cost online and offline, designing and running evaluations that measure accuracy, reliability, and cost on public and proprietary datasets, prototyping new capabilities and turning successful experiments into production components, investigating agent failures, identifying their causes, and developing fixes, and shipping features regularly with the team and contributing to team reviews owning increasing context as the Co-Op's project expands. The work will be a mixture of research and engineering, with the exact balance potentially changing week to week.
Requirements
- Enrollment in a master's degree program in computer science, machine learning, or a related field.
- Strong Python skills and experience reading and writing production-quality code.
- Hands-on experience developing agents through coursework, personal projects, research, or prior work.
- The ability to break down complex systems, reason from first principles, and develop practical solutions.
- Clear technical communication skills.
Nice To Haves
- Experience building agents, agent runtime systems, or MCP tools.
- Familiarity with evaluation frameworks or experiment-tracking tools.
- Previous internship or co-op experience shipping software.
Responsibilities
- Build and improve agents that use APIs, tools and large datasets.
- Rethink traditional research and software-development workflows using an agentic SDLC.
- Design evaluations for accuracy, reliability and cost online and offline.
- Design and run evaluations that measure accuracy, reliability, and cost on public and proprietary datasets.
- Prototype new capabilities and turn successful experiments into production components.
- Investigate agent failures, identify their causes, and develop fixes.
- Ship features regularly with the team and contribute to team reviews owning increasing context as the Co-Op's project expands.
Benefits
- Retirement benefits may be available after completing a set number of hours.
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What This Job Offers
Career Level
Intern
