Mechanical Design Integrations Backend Engineer

Foundation EGI is a MIT-born, venture-backed Silicon Valley startup building a real-life 'Jarvis'—an AI Copilot for design and manufacturing. The role involves building software that connects engineering intelligence to leading CAD platforms, designing APIs, and integrating CAD systems with cloud-native infrastructure to enhance product design and manufacturing.

Responsibilities:

• Translate CAD models into machine-readable engineering data
• Connect Siemens NX, CATIA, SOLIDWORKS and other CAD platforms with cloud-native AI services
• Build scalable APIs that allow engineering applications to exchange geometry and metadata
• Develop Python services that automate complex engineering workflows
• Design backend systems that manage CAD assemblies, parts, configurations and engineering metadata
• Partner with researchers building next-generation Engineering AI

Requirements:

• 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