Our client is building the first generative foundation models capable of performing the work of a licensed mechanical engineer. Rather than focusing on optimization or simulation tools, the company is tackling the actual design work engineers do: complex parametric modeling, constraint resolution, and manufacturing-aware geometry generation.
About the Role
This is a foundational technical hire. You'll own the geometry backbone of the company's generative CAD system, working at the intersection of computational geometry and applied AI. You will report directly to the Chief of Staff within a flat, low-bureaucracy organization where technical expertise directly shapes product and roadmap decisions.
This is not a CAD software or tooling role. It is deep infrastructure work: building the geometric foundations that allow AI models to generate valid, manufacturable designs.
What You'll Do
Design and build B-rep data structures and pipelines that power parametric CAD generation
Advance parametric geometry and constraint-solving systems, enabling AI models to understand and manipulate design intent
Apply CAD kernel expertise (Parasolid, ACIS, OpenCASCADE, or similar) to inform how generative models produce valid geometry
Build geometry processing systems for topology analysis, feature recognition, and design validation
Partner closely with researchers and engineers to define the geometric foundations of next-generation engineering AI
Directly influence technical strategy and product roadmap through your domain expertise
What We're Looking For
6+ years of hands-on experience in computational geometry or CAD kernel engineering (required); this is a hard requirement, not a nice-to-have
Deep expertise in B-reps, NURBS, parametric geometry, solid modeling, and surface modeling fundamentals
Strong C++ or Python skills applied to geometry processing and algorithm development
Production experience with a CAD or geometry kernel such as Parasolid, ACIS, or OpenCASCADE
Comfort with geometry algorithms and data structures, including mesh processing, point cloud operations, and topology analysis
A genuine passion for computational geometry and a builder's mindset suited to fast-moving, ambiguous environments
Preferred
PhD in computational geometry, physics, mathematics, or computer science
Domain experience in aerospace, robotics, or manufacturing, with an understanding of how geometry decisions affect real-world engineering outcomes
Published research or open-source contributions in geometry, shape analysis, or related fields
Why Join
Work on the core geometry engine enabling AI to perform licensed mechanical engineering work, not another CAD tool
Build on a proven foundation with a clear path to a commercial product
Join a dense, expert team with Series A momentum and a clear path to Series B
Operate with full technical ownership in a flat structure with no layers of bureaucracy
Competitive compensation reflecting the specialization this role demands