Job Description

SOURCE is an AI Native Operating System for Energy Engineering · Founded out
of Stanford + U.S. DOE · San Francisco Bay Area (in-person or remote) ·
Founding equity, no cash today

Unleash the energy capacity already trapped inside America's buildings, by
putting physics based energy models and frontier AI to work on the engineering
workflows that unlocks it.

Why this role exists

For the first time in almost 30 years, U.S. electricity demand is climbing. AI
factories are accelerating it, and the grid can't keep up, the North American
grid reliability outlook is in the red. The fastest new capacity isn't a power
plant that takes a decade to build. It's the behind-the-meter energy systems
already sitting inside every commercial building: HVAC, lighting, controls,
solar, storage.

That capacity is trapped behind slow, manual engineering. A commercial
building portfolio energy upgrade takes months to engineer, burns $500k in
labor, and stalls $50M contracts in the pipeline. Millions of profitable
energy projects never get built because the engineering doesn't scale.

What SOURCE is

SOURCE is the AI-native operating system for behind-the-meter energy
infrastructure, the engineering intelligence layer that turns messy site data
into finance-ready energy projects in days, not months.

Where we are today

Founded by experienced energy project developers out of Stanford and the
National Labs. 3M+ sq ft of commercial buildings under active development. We
developed energy projects directly to understand the context, now we are
bringing Vertical AI for multinational engineering firms to 10x their
productivity.

The role

You are the founding CTO. You own the software.

This is a build seat, not a manage seat. You'll architect the system, write
the code that matters, and hire the team around you (AI/data engineers, an
energy modeler, an iOS developer). You'll partner with our CSO, who owns the
energy-science domain — you own the platform, the AI systems, the data, and
the org that ships them.

What you'll own and build

AI agents: Task-specific agents that run the engineering work, from utility-
bill analysis to proposal generation.

Multi-modal AI: An iOS field app that turns photos, voice, and equipment
nameplates into structured project data.

Automatic building energy modeling: Convert messy site data into a simulatable
digital twin of a building's energy systems.

The engineering organization: Hire the team, set the technical bar, ship to
production weekly.

The AI-native project engineering platform — own the full architecture: the
system real engineers depend on to win contracts.

Must-haves

You've shipped AI systems to production, agentic pipelines or LLM systems that
real users rely on, not prototypes that die in a notebook.

Strong systems and data engineering. You can architect from a blank page and
still be the best engineer in the room when it counts.

You move toward ambiguity, talk to customers directly, and have a forward-
deployed instinct — you'd rather sit next to an engineer at a job site than
guess at the spec.

You want to build a company, not own a feature.

Bonus, not required

Energy, buildings, or simulation background, EnergyPlus / OpenStudio, load
modeling, utility interval data, ECMs, behind-the-meter assets.

Native iOS / mobile capture experience, or geospatial and computer-vision work
on real-world data.

Compensation

This is a founding, equity-only seat. You'd be taking founder-level equity and
founder-level risk to build the platform a multi-billion-dollar engineering-
labor market will run on.

If you need a salary on day one, this isn't the seat. If you want to own a
generational company at the intersection of AI and energy, it is.

Build the layer that unleashes America's stranded energy capacity. Built in
the workflow. Proven in the field. Ready to deploy.