Founding Engineer

Physical AI; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Founding equity

Visa sponsorship

Job summary

Physical AI in San Francisco is building models and tooling to accelerate hardware design. The founding engineering team will own core architecture and productionize physics-informed models on real boards.

You will shape the tech stack, integrate with engineers' tools, and design practices that allow a small team to operate like a larger one. Visa sponsorship available and meaningful founding equity offered.

Qualifications

• Experience delivering hardware-focused software stacks.
• Ability to design end-to-end architectures for boards and systems.
• Strong bias for shipping with reliable CI/CD workflows.

Responsibilities

• Own product architecture, services, and storage end-to-end.
• Shape tooling, workflows, and vendor selection for the stack.
• Integrate engineering tools and turn research models into production.
• Define internal engineering practices and set hiring bar.

Skills

Hardware design

System architecture

DevOps culture

CI/CD

Tools

CI/CD pipelines

VCS

Job description

The technology used to design hardware is some of the most complex in existence, and it hasn't changed much in decades. Engineers spend enormous amounts of time on setup, scripting, debugging failures, and waiting on runs that take hours or days. A single board program can drag on for 9 to 12 months, mostly because nobody catches a problem with the board until physical testing. By then it's late, and it's expensive to fix.

General-purpose AI and LLMs don't understand circuit physics, so we're building our own models in-house, from the ground up, trained specifically on how signals and fields actually behave on a board. We take schematics straight from the tools engineers already use, run our AI to generate fabrication-ready boards, and hand them back. No rip-and-replace, no throwing away twenty years of muscle memory.

Our vision is simple to say and hard to build: hardware design should move at the speed of software. Chips and boards aren't easy, but the tools around them just haven't kept pace with everything else.

We're a very small technical team by design. We've grown a company from pre-product to nine figures in annual revenue, and grown engineering orgs from 3 people to 50. We've published AI research with real citations behind it and hold multiple patents. We're now hiring the founding engineers on our team * not the fortieth * and you'd be building next to us from day one.

What you'll own

• The product architecture, services and storage solutions end-to-end, with nobody between your decision and production.
• Technical stack and productivity tools, selecting key vendors in our technical stack and contributing to the developer flow, from agentic systems to reliable CI processes.
• Integrations with engineering tools and services our customers already run, hardened enough that switching to us feels like nothing changed.
• Turning our research team's physics-informed models into production systems engineers trust with real boards.
• Design the agentic engineering practices this company runs on internally * the tooling and workflows that let a two-person team ship like a twenty-person team.
• Set the engineering bar for every hire that comes after you, because for a while, we will be the bar.

What we do

The technology used to design hardware is some of the most complex in existence, and it hasn't changed much in decades. Engineers spend enormous amounts of time on setup, scripting, debugging failures, and waiting on runs that take hours or days. A single board program can drag on for 9 to 12 months, mostly because nobody catches a problem with the board until physical testing. By then it's late, and it's expensive to fix.

General-purpose AI and LLMs don't understand circuit physics, so we're building our own models in-house, from the ground up, trained specifically on how signals and fields actually behave on a board. We take schematics straight from the tools engineers already use, run our AI to generate fabrication-ready boards, and hand them back. No rip-and-replace, no throwing away twenty years of muscle memory.

Our vision is simple to say and hard to build: hardware design should move at the speed of software. Chips and boards aren't easy, but the tools around them just haven't kept pace with everything else.

We're a very small technical team by design. We've grown a company from pre-product to nine figures in annual revenue, and grown engineering orgs from 3 people to 50. We've published AI research with real citations behind it and hold multiple patents. We're now hiring the founding engineers on our team * not the fortieth * and you'd be building next to us from day one.

You might thrive if you...

• Have taken something from zero to one before and you want to do it again - this time with the equity, ownership, and title to match what you're actually doing.
• Understand the real trade-offs in storage, compute, and system architecture and optimize for the problem in hand vs the best theoretical solution.
• Have a good approach in build vs buy decisions and understand software maintenance costs, and scaling complexities.
• Have experience with * or are eager to grow into * agentic systems: dedicated containers, multi-agent orchestration, agent review, multi-model task distribution.
• Like the idea of getting fluent, fast, in building foundational models (not just wrappers) alongside a PhD-heavy research team, even though it's not your background yet.

*human generated em dash

Details

• Full-time
• San Francisco, five days per week onsite
• Reports directly to a founder
• Meaningful founding equity
• Visa sponsorship available