Location:
(
New York City
,
NY
)
Salary:
$
180k
- $
225k
Founding Engineer
$180K–$225K based on qualifications · Equity up to 0.5%
About the company
Most engineering problems have a known solution. This one does not.
The company is building digital replica employees agents that learn by observing a human work for weeks, extract the underlying logic behind what they do, then execute that same process autonomously across the same screens and the same files, at unlimited scale. A computer-use agent carrying deep, learned knowledge of how one specific person finishes one specific job. The product being sold is labor, delivered as software.
The core challenge: take observations of a top performer and turn them into a deployable replica that generalizes that person's decision-making across novel situations inside arbitrary software. It is a machine learning problem, a systems problem, and a product problem at the same time, and none of the pieces are solved.
The founding team is three military-trained engineers who came out of MIT and Amazon. They spent the last decade converting human labor into software, automating 10 million hours for the Department of Defense. They are now pointing that work at healthcare administration one of the most expensive and most broken operational systems in the U.S. economy. Four major customers have signed in 2026 alone, including one of the largest health systems in the country. The demand is real, and the company is building against it in real time.
Techstars-backed and SBIR-funded.
About the role
This engineer helps build the core platform from the ground up: AI orchestration, computer-use workflows, cloud infrastructure, deployment systems, reliability tooling, and the product surfaces customers depend on daily. The role carries architecture decisions, end-to-end ownership of critical systems, and work across the full stack — turning messy operational reality into something elegant, measurable, and durable.
It is a high-leverage seat for someone who wants broad ownership and genuine technical influence. The right person moves comfortably between product, infrastructure, and AI behavior, and cares about shipping cleanly, debugging carefully, and building systems that hold under pressure.
Good fit if