TL;DR: If you:
Have yourself designed complex physical systems;
Can translate customer workflows into a coherent, scalable product;
Have a rigorous understanding of AI models, agents, evals, and failure modes;
Have taken an AI product from early capability to sustained use;
Are as happy and capable being hands-on, as you are building and leading a team;
Share our vision of an AI engineer for the physical world…
… 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 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:
This is one of the most impactful roles in the company. You will work alongside the CEO to refine and translate the product vision for Archie into an actionable roadmap and strike the delicate balance between vision-driven and customer-driven product development. You must bring to the role a thorough understanding of how complex physical products are designed today, as well as a nuanced perspective on the capabilities and limitations of modern AI models and harnesses. You will be a key driver of our product strategy and execution, and as such you must be a true believer in our mission to build an engineering ASI for the physical world.
About the role:
Continuously map our ambitious vision into a focused product strategy and feature roadmap.
Embed with customers, understand their workflows, and inject customer use cases into the product roadmap.
Develop feature specifications and requirements alongside the engineering teams.
Work alongside engineering leaders to drive overall product architecture.
Lead product from emerging AI capability to trusted, sustained use in real engineering environments, setting a rigorous bar for performance, evals, reliability, and graceful failure modes.
Build and lead a world-class product team—while staying deeply hands-on with discovery, design, and delivery.
About you:
You have intimate familiarity with engineering design for some class of complex systems. If the complex systems align with our target product verticals: data center cooling and power systems, automotive, aerospace and defense—so much the better.
You are deeply embedded in the AI ecosystem and have a thorough understanding of how modern AI works, its limitations, and its failure modes.
You’ve taken an AI product from early capability to sustained customer adoption.
You love the 0->1 part of the journey, being hands on, attracting top talent, and motivating a team.
You share our conviction that AI building the physical world will be beneficial and transformative for the human experience.
Location:
Remote (US/Canada) or in-office in San Mateo, CA. Remote employees spend one week out of six working together on-site in our San Mateo office. Relocation support available.
Benefits:
Competitive salary, bonus, meaningful equity ownership, healthcare, dental, vision, 401(k) match, and unlimited PTO.
Interview process:
Introductory call (30 mins)
Biographical/behavioural interview (45 mins)
Case study interview (60 mins)
CEO interview (30 mins)
Skills Required
- Experience designing complex physical systems
- Ability to translate customer workflows into a coherent, scalable product
- Thorough understanding of modern AI models, agents, evaluation methods, limitations, and failure modes
- Experience taking an AI product from early capability to sustained customer adoption
- Ability to work hands-on across product discovery, design, and delivery while building and leading a team
- Experience embedding with customers and incorporating engineering workflows and use cases into product strategy
- Experience developing feature specifications and product requirements with engineering teams
- Experience driving product architecture with engineering leaders
- Experience establishing standards for AI performance, evaluations, reliability, and graceful failure modes
- Familiarity with data center cooling and power systems, automotive, aerospace, or defense engineering
- Experience with 0-to-1 product development and attracting and motivating top talent
What We Do
Building engineering AGI for the physical world.









