Feeny
Foundation EGI

Mechanical Design Integrations Backend Engineer at Foundation EGI (Boston, MA)

Foundation EGI· Boston, MA· $110k–$175k·

Role details

Salary
$110k–$175k
Work type
Remote
Employment
Full-Time

Job description

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.

We're looking for a Senior CAD Backend Engineer to build backend integrations and automation for our AI Engineering platform. You'll connect CAD systems to cloud-native services, streamline mechanical design workflows and develop Python based backend features.

Responsibilities

You'll help build systems that:

-

  • 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.

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

Why work at Foundation EGI

  • Small team, hard problems: The careers page explicitly pitches "a small team solving hard problems at the intersection of mechanical engineering and AI."
  • Remote-friendly: All open roles are open to remote candidates unless otherwise noted.
  • Open roles: Hiring across engineering, product, and research (posted on the Lever careers page under "Foundation LLM Technologies").
  • Research-backed culture: Founders and team come from MIT CSAIL and leading tech companies (Mercari, Samsung, PayPal, Apple, Flexport, Honda Drivemode), combining academic rigor with scaled product experience.
  • Mission-driven work: Opportunity to build AI infrastructure for an underserved market — physical product/manufacturing companies that still generate documentation by hand.
  • Global, multilingual team: Team members span the US and Asia and bring experience leading global engineering and product organizations.

Application questions