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
Similar Jobs
Artificial Intelligence • Cloud • Software • Infrastructure as a Service (IaaS)
Own the technical lifecycle and operational health of a global high-density GPU fleet. Validate hardware, benchmark performance, monitor uptime and SLAs, automate operations using LLMs/agents, perform deep network and system-level troubleshooting, coordinate incident communications, and support infrastructure partners.
Top Skills:
Ai AgentsBashDatadogDockerGo (Golang)GrafanaInfinibandLinuxLlmsNvidia Software StackPrometheusPythonRdmaRoce
Artificial Intelligence • Cloud • Consumer Web • Productivity • Software • App development • Data Privacy
Lead and scale Product Marketing operations: build operating models for messaging lifecycle, portfolio and roadmap visibility, PMM launch governance, cross-functional decision rights, templates, reporting, and AI/automation-enabled workflows to improve launch readiness and go-to-market execution.
Top Skills:
AutomationData ReportingKnowledge-Management SystemsResponsible Ai
Cloud • Information Technology • Security • Software
Sell LogicGate's AI-driven GRC platform to large enterprises by building territory plans, prospecting, managing full sales cycles, partnering with Solutions Engineers for demos, negotiating deals, and advising customers on best practices to drive pipeline and revenue.
Top Skills:
BpmGrcLogicgateMarketing AutomationPipeline AnalyticsSales AutomationSalesforce
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
