Technology is no longer the limiting factor for automating knowledge work. Deployment is. A frontier lab ships a capability, and 18 months later a handful of Fortune 500s have it in production and everyone else has a pilot. The gap isn't model quality. It's that deploying AI into a real business means learning a workflow nobody wrote down, integrating with software from 2003, and hitting a reliability bar the model alone doesn't meet.
Ventura closes the deployment gap for industrial operations, as a configurable product, not a consulting engagement. We started with one product: quoting and order entry for industrial distributors. We're live with customers doing billions in revenue, moving thousands of truckloads of material across the U.S. every day.
Those customers are already asking us to automate the next five processes. Growth is limited by how much we can ship, not by demand. We're hiring founding engineers, full time, in person in SF.
Swen (CEO): exited a B2B SaaS in the same industry, ex-BCG, Harvard MS/MBA. Jack (CTO): founding engineer at Develop Health (0 → $7m ARR with 5 people), creator of Magentic, Imperial College London.
You'd be our first founding engineer.
You’ll own problems end to end: talk to customers, understand how they work, decide what we should build, and then build it. You’ll work across customer-facing features, AI agents, integrations, and infrastructure. Along the way, you’ll improve the evals, tests, and tooling that make each new customer implementation faster and more reliable.
- Week one: shipped your first feature to a live customer
- Month one: got on a call with a customer, designed and implemented a feature to solve a problem for them
- Quarter one: owning a meaningful surface area of the product, end to end
- Full stack experience: NextJS, TypeScript, Python, Google Cloud
- Understand how to build production-ready agents: context engineering, tool design, evals, …
- Can talk directly with customers, ask good questions, and get to the root of their problems
- Ship fast without lowering the quality bar
- Stay on the bleeding edge of AI tools to increase leverage, without outsourcing their engineering judgment
- Like owning the whole problem rather than working from a narrowly defined backlog
We fully support visa sponsorship and relocation to San Francisco. We’ll help with anything that prevents you from doing your best work.