You'll build the software that connects engineering intelligence to the world's leading CAD platforms.

If you've ever written Python that automated Siemens NX, CATIA, SOLIDWORKS, or Creo—or built backend services that process engineering design data—you'll likely find this work exciting.

You'll design APIs, integrate CAD systems with cloud-native infrastructure, and build the backend powering AI-driven engineering workflows used to accelerate product design and manufacturing.

This role combines software engineering, CAD automation, backend architecture and mechanical engineering in ways that are rarely found together

• BS/MS in Mechanical Engineering, Computer Science, Software Engineering, or a related technical field.
• 5+ years of experience building and maintaining backend services and production software.
• Strong Python engineering skills with experience writing clean, scalable, and maintainable code.
• Experience developing software integrations using commercial CAD APIs, such as Siemens NX Open, CATIA, SOLIDWORKS API, Creo Toolkit, Autodesk Inventor API, or similar engineering platforms.
• Experience building cloud-native applications, backend APIs, and data models (including Protobuf).
• Experience working with 3D engineering data, CAD models, assemblies, and related engineering file formats.
• Strong written and verbal communication skills with the ability to collaborate across engineering, research, and product teams.

• You've built software using at least one commercial CAD API:

  • • Siemens NX Open
    • CATIA
    • SOLIDWORKS API
    • Creo Toolkit
    • Autodesk Inventor API

• Experience developing CAD automation tools, plugins or engineering software integrations.
• Familiarity with computational geometry, CAD workflows, PLM systems, or engineering data pipelines.
• Experience working with large-scale 3D models, assemblies or complex engineering datasets.
• Strong programming experience in C++ alongside Python.
• Experience designing and implementing gRPC-based APIs and distributed services.
• Experience building and deploying applications using Docker and Google Cloud Platform (GCP).
• Experience implementing logging, monitoring, observability, and production debugging practices.
• Experience partnering with mechanical engineers, researchers, or AI/ML teams to build engineering applications.
• Passion for building software at the intersection of CAD, Mechanical Engineering, Backend Systems, and Engineering AI.