Build the AI that makes things.
Gottlieb is the Engineering AI company, turning intent into a manufactured, verified, physical product. Join the team proving it at the production-approval gate every regulated part must clear.
Generative AI made content. Agentic AI made action. We are building the one that makes things: the first AI whose output is a manufactured, physical part. It is early, the stakes are real, and the work is hard in the way that matters. If you want your work to end up in parts that ship, build with us.
What you would be part of.
A small team carrying a large claim, calmly. We prove things before we say them, we own what correct means, and we put the engineer above the machine. The work is rigorous because in safety-critical engineering, rigour is the product.
Proof over promises
We ship parts before we preach. Every claim is sourced or modelled and labelled as such. You will never be asked to oversell.
Own what correct means
We do not generate and hope. We build the verifier that decides correctness and hold ourselves to it. You own the standard, not a wrapper on someone else's model.
Hard problems, real stakes
Production approval for regulated parts: PPAP, FAI, 510(k). The documentation failures behind real recalls. The margin for error is slim, which is the point.
The engineer is the hero
The system augments judgment and never replaces the sign-off. We elevate the expert; a human stays in command of anything safety-critical.
Early to a new category
Engineering AI is the empty slot on the AI map, after generative and agentic. Being early to the first AI that makes things is the opportunity.
Why it is worth it.
The reason to join is not the perks. It is the chance to put your name on the first AI whose output you can hold, alongside a team that has done this before.
Work that ships: what you build clears the gate that lets real parts enter production, live with automotive partners today.
Built by two halves: the domain authority who ran production approval at Daimler and the AI leader who built generative AI and evaluation at Meta.
Ownership: small team, large surface. Your decisions are visible in the product and in the proof.
Depth: encode the standards regulated industries already enforce, and the verifier that decides correctness over them.
Fair terms: competitive compensation, real health benefits, and flexible arrangements, stated plainly.
Common Questions
We've covered the basics. For more, drop us a line.
We hire engineers who build verifiers, encode standards, and ship to regulated manufacturing, plus domain experts from automotive, aerospace, and medical. We are building Engineering AI, not generic generative AI.
Yes, fully remote or hybrid, with tools across AWS, Azure, and GCP for seamless collaboration.
Model-agnostic: OpenAI, Anthropic, Google models; cloud-agnostic: AWS, Google Cloud, Microsoft Azure for flexibility.
Through inclusive recruiting, bias training, and employee resource groups.
Early-growth startup with funding, scaling our AI platform for engineering impact.
Absolutely—use the form to share your resume and why you're interested.
A blend of innovation, ethics, and fun—working on AI that matters.