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Founding Full-Stack Engineer, AI Agent Products

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Seeking a founding-level Full-Stack Engineer to build zero-to-one AI agent products at a new San Francisco AI lab. You will own end-to-end product areas spanning user interfaces, agent workflows, model orchestration, and infrastructure while working directly with users. Candidates need exceptional engineering skill, strong product judgment, 2+ years of experience, and a founder mentality with high ownership.

Key Highlights
Founding-level full-stack role building zero-to-one AI agent products at a brand-new AI lab.
Own end-to-end product areas including interfaces, agent workflows, model orchestration, and infrastructure.
Work directly with users and help shape product, architecture, and culture as an early team member.
In-office in San Francisco with visa sponsorship supported; no relocation package is offered.
Key Responsibilities
Build the product that lets users hand off complex outcomes to long-running agents and track them.
Own zero-to-one AI product areas end to end.
Build across user-facing interfaces, agent workflows, model orchestration, and infrastructure.
Turn frontier model capabilities into reliable products that solve real user problems.
Work directly with users to understand their workflows and iterate quickly.
Help shape product, architecture, and culture as an early team member.
Technical Skills Required
Full-Stack Engineering AI Model Orchestration Infrastructure
Benefits & Perks
Visa sponsorship supported
Nice to Have
Agentic-product pedigree at top AI coding and agent companies (e.g., Cursor, Cognition, Decagon, Sierra).
Zero-to-one founder or early-team experience.
Olympiad, quant, or world-class competitive background.

Job Description

About the company:

Our client is a newly founded AI lab building a new class of agents. These agents take ownership of complex goals and work on them autonomously for days, then months, and eventually indefinitely. The founding team comes from some of the strongest AI research and engineering environments in the world. Their first application is self-improving products: agents that learn what customers are trying to achieve, build and deploy solutions, measure the results and keep iterating.

About the role:

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