AI Engineer

P-1 AI; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive salary

Equity ownership

Healthcare

Dental

Vision

401(k) match

Unlimited PTO

Job summary

P-1 AI, located in San Mateo, CA, is seeking an experienced team member to develop innovative solutions for our AI engineering agent, Archie. This role involves collaborating with research scientists, enhancing model capabilities, and integrating various engineering tools.

The ideal candidate should have profound experience in transitioning AI prototypes to production, deep learning, and proficiency in Python. We offer competitive salary, equity ownership, and a range of health benefits.

Qualifications

• Experience transitioning AI research prototypes into delivered products.
• Deep understanding of machine learning and large language models.
• Fluent in Python and common agentic frameworks.

Responsibilities

• Develop agentic engineering reasoning for real engineering design problems.
• Build, improve and maintain agentic harness and tool integrations.
• Analyze production traces to identify failure modes.
• Collaborate with research scientists to enhance model capabilities.

Skills

AI product development

Deep learning

Machine learning fundamentals

Python proficiency

Experience with physical systems

Tools

LangChain

Job description

TL;DR

• 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…

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 are backed in our mission by some of the top venture investors and AI luminaries.

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)