
Building engineering AGI for the physical world.
Focus: Engineering AGI (AGEI) for the built/physical world
Product: Archie — an AI engineer for quantitative and spatial reasoning in physical product design
Funding: $23.0M seed (Apr 2025) led by Radical Ventures
Founding: Founded 2024; emerged from stealth April 2025
Leadership: Paul Eremenko (Co‑founder & CEO); Adam Nagel (Co‑founder & Head of Engineering)
Team size: 27 employees
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Artificial general engineering intelligence (AGEI) for the built/physical world
2024
Software Development
$23.0M
Participating investors included Village Global, Schematic Ventures, Lerer Hippeau and individual investors such as Jeff Dean, Peter Welinder, Sergey Gorbunov, and Bob van Luijt (8 investors total).
About You
About Us We are building an engineering AGI. We founded P-1 AI with the conviction that the greatest impact of artificial intelligence will be on the built world. Our first product is Archie, an AI engineer capable of quantitative intuition over physical product domains and engineering tool use. Archie initially performs at the level of an entry-level design engineer but rapidly gets smarter and more capable. We aim to put an Archie on every engineering team at every industrial company on earth.
Our founding team includes the top minds in deep learning, model-based engineering, and industries that are our customers. We closed a $23 million seed round led by Radical Ventures that includes a number of other AI and industrial luminaries (from OpenAI, DeepMind, etc.).
In Summary
About The Role We are a small team tackling an ambitious problem. If we are successful, it will change the course of history. As such, we have a very high talent bar and are looking for people who have done something remarkable.
This role builds the physics simulators that teach Archie how the real world works. You will develop first-principles, acausal models of thermofluid and electrical systems and use them to generate large-scale synthetic datasets that power Archie’s reasoning about physical systems.
You will work on chillers, air handlers, cooling towers, hydronic networks, switchboards, transformers, and distribution systems—sweeping your models across thousands of operating conditions, fault modes, and design variants. The fidelity of your simulations directly determines the capabilities of our AI.
You will collaborate closely with ML engineers to ensure simulation outputs translate into real-world performance.
We don’t care if you’ve done it before. We just need you to be brilliant, mission-driven, and thirsty to learn.
This role can be either remote (based in the US or Canada and with existing work authorization) or based in our SF office. If you are remote, you should plan to spend one week out of six co-working with the rest of the company in our SF office. We will support relocation for candidates interested in moving to SF.
Compensation $150 - $200k… for now. This role includes a significant equity component. We are an early-stage startup, so we favor equity over cash in our current compensation philosophy. You should too, or an early-stage startup might not be for you. That said, we expect cash compensation to progress quickly as the company matures.
Our benefits include healthcare, dental, and vision insurance, 401k with employer matching, and unlimited PTO.
Interview Process