TL;DR: If you:
have a demonstrated track record of turning ambitious AI ideas into products people actually use;
move effortlessly between research and engineering;
have shipped something extraordinary, at work or outside of it;
are relentlessly curious about how things work…
… you should apply for this role!
About P-1 AI:
At P-1 AI, we are building an AI engineer agent for the physical world named Archie. We maximize Archie’s anthropomorphism so that he fits seamlessly into existing engineering teams and workflows in the form factor of a human engineer. Archie today is at the level of a junior mechanical and electrical engineer, with a quantitative intuition over the product design space and the ability to use complex engineering tools—the same tools his human teammates use. Archie's tech stack includes a custom agentic harness, structured design representation, continual skills learning, and small custom post-trained models (SFT and RLVR) using proprietary semi-synthetic training data sets and environments which create a deep competitive moat. Our ultimate aim is to build engineering ASI. We recently announced a $50 million Series A financing led by NEA, which added former General Electric CEO Jeff Immelt to our board. The round also included the addition of several AI luminaries from Anthropic and Nominal to our existing angel investors from Google and OpenAI.
About the opportunity:
We're building toward engineering ASI, and every capability we ship moves us closer. You'll work on the fundamental systems that allow Archie to reason, learn, and operate in complex engineering domains—taking ideas from whiteboards and papers all the way to production deployments.
About the role:
Develop agentic engineering reasoning through methods ranging from structured representation to formal methods to solve real engineering design problems.
Build, improve and maintain our agentic harness and its tool integrations.
Ground the quality of your work by regularly running evaluations and tests.
Analyze production traces to identify failure modes and investigate customer-reported bugs.
Collaborate with research scientists to identify gaps in current model capability, help develop custom models and transition them into the core product.
Stay up-to-date with new agentic frameworks and capabilities, and bring promising ideas into reality.
About you:
Experience transitioning AI research prototypes into delivered products.
Deep learning experience with strong fundamental understanding about machine learning, large language models, and agentic harnesses.
Fluent in Python and common agentic frameworks (for example LangChain).
Experience building physical systems (Aerospace, Mechanical, Robotics, other).
Location:
Onsite in San Mateo, CA. Relocation support available.
Benefits:
Competitive salary, meaningful equity ownership, healthcare, dental, vision, 401(k) match, and unlimited PTO.
Interview process:
Initial screening call (30 mins)
Biographical/behavioural interview (45 mins)
Technical interview (60 mins)
CEO interview (30 mins)
