Senior Software Engineer, Platform CAM

CAM connects geometric intent with physical processes. You’ll build the software infrastructure that lets process experts express where an operation acts, what effect it should produce, and which constraints it must satisfy.

The challenge is to turn that knowledge into reusable representations, algorithms and interfaces. These must extend beyond familiar etching or 3D-printing workflows to support different ways of shaping, treating and assembling materials. Success means new processes can build on shared geometric capabilities while preserving the assumptions and behavior that make each process distinct.

You’ll bring strong software engineering and deep interest in geometric reasoning, working with experts who bring the physics and process knowledge.

AI fluency is central: use agents throughout development while owning the decisions, code and results you accept.

• Build and evolve Go and Python software infrastructure for representing geometric intent and generating physical-process operations.
• Develop reusable geometric representations and algorithms for shapes, regions, coordinate frames, spatial relationships, and process planning.
• Work with process experts to turn their knowledge into explicit models, constraints, interfaces, and acceptance criteria, including effects that vary over space or time.
• Extend shared capabilities to new processes; keep process-specific behavior explicit and integrate with machine software and fab coordination.
• Test geometric and software correctness, make generated results reproducible, and validate assumptions with experts and physical measurements.
• Use AI throughout investigation, design, implementation, testing, and documentation; inspect changes and verify results.

• Production software ownership, typically 8+ years for the senior target; productive Python and strong in Go or C++, with readiness to work in Go. Level is based on demonstrated scope and ability.
• Experience in, or a demonstrated deep interest in, geometric reasoning: representing shapes and spatial relationships, choosing useful abstractions, and reasoning about their limits.
• Evidence of designing reusable software infrastructure, simplifying complexity, and testing and safely evolving systems with clear interfaces.
• Strong AI fluency: provide context, challenge proposals, inspect code and meaningfully test accepted work.
• Ability to work with domain experts, make assumptions explicit, and turn their knowledge into testable software behavior.
• Care with units, coordinate frames, tolerances and approximation; willingness to learn unfamiliar physical processes and work directly with fab equipment.
• BS in CS or a related field, or equivalent practical experience.