Build backend services and APIs that integrate commercial CAD platforms (Siemens NX, CATIA, SOLIDWORKS, Creo, Inventor) with cloud-native AI services. Translate CAD models into machine-readable data, automate engineering workflows in Python, manage assemblies, parts, configurations, and partner with research teams on Engineering AI.
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
ABOUT US: We are a MIT-born, venture-backed Silicon Valley startup building a real-life 'Jarvis'—an AI Copilot for design and manufacturing. Our goal is to utilize advanced AI, physics simulation, and computer graphics to reduce costs and improve engineering productivity across all steps of the design and manufacturing process.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.
You'll help build systems that:
What we're looking for
- 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
Bonus Points
- 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.
Our tech stack
- Google Cloud
- Python, TypeScript
- Protobuf, gRPC
- Next.JS, React.JS
- GitHub Actions
- Docker, Kubernetes, Spinnaker
- PostgreSQL
Foundation EGI Boston, Massachusetts, USA Office
Boston, MA, United States
Similar Jobs
.png)
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
Partner with Institutional senior leadership to structure ambiguous strategic problems, build quantitative business cases and financial models, translate data into executive recommendations, design experiments to validate hypotheses, drive implementation end-to-end, and improve processes, frameworks, and operational tooling to shape product and go-to-market strategy.
Top Skills:
Dune AnalyticsEtherscanGenerative AiHexLookerSQLSuperset
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Lead product vision, roadmap, and delivery for Product and Services Analytics. Drive requirements, prioritize backlog, partner with engineering on technical solutions, define KPIs, engage executives and stakeholders, mentor junior product staff, and guide go-to-market and documentation for analytics features in a cybersecurity context.
Top Skills:
AIAPIsData PipelinesSalesforceSnowflakeSQLTableau
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Build and own a vendor schema registry and semantic validation pipeline that ingests OpenAPI/Swagger/Smithy specs, tracks schema evolution, detects semantic and breaking changes, and provides SDKs and developer tooling to safely map vendor APIs into a canonical knowledge graph used by downstream teams.
Top Skills:
Ai TechnologiesGoGraph Data ModelsJson SchemaOpenapiOwlPythonRdfRustShaclSmithySparqlSwagger
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
