Founding Engineer

This is a founding engineering position at an early-stage AI/ML startup building systems that help hardware and electrical engineering firms move faster by turning decades of accumulated domain knowledge into intelligent, compounding technology. You will partner directly with the CTO to own the full technical stack, from architecture to production, inside real customer programs at defense and medical device companies.

Design and build the core system architecture that integrates AI agents with CAD, CAE, and PLM tools while meeting the security requirements of defense and medical customers.

Own end-to-end engineering execution including design decisions, production delivery, reliability, observability, evaluation suites, regression testing, and on-call operations.

Ship your first production AI workflow into a live customer program, one that engineers use and depend on weekly.

Build evaluation and training loops that improve the system from simulation runs, test data, engineer corrections, and field outcomes, including reinforcement learning grounded in real physics.

Spend time embedded with engineers at partner companies to understand where the system fails against real deadlines, and translate those learnings into platform capabilities.

Expand the platform across multiple operating companies with measurable cycle-time reduction on at least one product line.

Help build and mentor the small engineering team that grows around you.

4 or more years shipping software to production, including systems that real customers depended on daily.

Proven experience putting AI into production: shipped LLM agent workflows that call real tools, handle failures, and are held to rigorous evaluation suites.

Strong Python and backend or ML systems engineering skills; comfort picking the right tool for the job.

Experience designing system architecture for agent orchestration and tool integration.

Ability to design rigorous evaluations and judge honestly when the answer is retrieval, fine-tuning, reinforcement learning, or plain software.

Production delivery experience including observability, regression testing, and on-call operations.

Strong CS fundamentals, ideally from a rigorous academic background.

Prior experience at a high-growth or early-stage company in AI, industrial software, autonomous systems, or developer infrastructure is a strong plus.

Experience with reinforcement learning, fine-tuning, simulation, robotics, physical-world AI, or domain-specific tools such as CAD, CAE, or EDA is a bonus.

Comfortable earning trust with domain experts on a shop floor as well as with technical leadership.

US citizen or permanent resident; visa sponsorship is not available.

Willing to travel to partner operating companies as needed.