UniversalAGI

UniversalAGI

AI Product Engineer

San Francisco

Sponsorship not specifiedDetected 36 days ago
TypeScriptPythonReactNext.jsFull-Stack DevelopmentDatabricksMachine LearningDeep LearningPyTorchLLMsUI DesignANSYSResearchLeadershipCommunicationCollaboration

About the role

  • You'll work closely with the CEO and founding team to turn research into repeatable, scalable, reliable systems - internally and in customer infrastructure.

Responsibilities

  • Ship End-to-End: Own and ship features across the full stack, including frontend, backend, databases, cloud services, APIs, and the UI
  • Design Core Abstractions: Build clean, reusable templates so power users can move fast, while ensuring new users can get started in minutes
  • Iterate on Feedback: Collect user feedback, iterate rapidly, and maintain strict product reliability and backwards compatibility as we scale our customer base
  • Collaborate Globally: Partner hand-in-hand with the founding team and engineering leadership to define product scope and architecture
  • Strong SWE Fundamentals: Excellent intuition for clean componentization, organized code architectures, user experience, and visual design
  • UniversalAGI is building OpenAI for Physics.
  • We're building foundation AI models for physics that enable end-to-end industrial automation from initial design through optimization, validation, and production.
  • We're building a high-velocity team of relentless researchers and engineers that will define the next generation of AI for industrial engineering.
  • UniversalAGI is hiring an AI Product Engineer to own our customer facing product across the entire stack.
  • In this role, you will build and own the end-to-end platform that engineers use to train and host physics models.

Requirements

  • End-to-End Production Ownership: Proven track record of shipping customer-facing products, with deep ownership over frontend, backend, and database layers
  • PyTorch is not required
  • Product Instinct: Ability to hold the user journey clearly in your head while evaluating complex technical tradeoffs
  • Ability to earn respect through hands-on technical contribution
  • Stack Fluency: Deep technical comfort with Python on the backend, alongside React, TypeScript, and Next.js on the frontend. Comfortable navigating databases and cloud APIs. PyTorch is not required

Nice to have

  • AI/ML Integration: Hands-on experience integrating AI components into customer products (e.g., LLMs, agents, or ML-backed product features)
  • Domain Context: Prior experience or background with 3D applications, CAD, physics simulations, or engineering tooling domains
  • Startup DNA: Prior early-stage startup experience (0 to 1 product development)
  • Technical Respect: Ability to earn respect through hands-on technical contribution
  • Intensity: Thrives in our unusually intense culture - willing to grind when needed
  • Customer Obsession: Passionate about solving real customer problems, not just publishing papers
  • Deep Work: Values long, uninterrupted periods of focused work over meetings
  • High Availability: Ready to be deeply involved whenever critical issues arise

Skills

  • Proven track record of shipping customer-facing products, with deep ownership over frontend, backend, and database layers

Compensation

  • Competitive Salary + Equity

Benefits

  • Competitive compensation and equity
  • Competitive health, dental, vision benefits paid by the company
  • Flexible vacation
  • AI tools stipend
  • Monthly commute stipend
  • Monthly wellness / fitness stipend

Company info

  • AI startup based in San Francisco and backed by Elad Gil (#1 Solo VC), Eric Schmidt (former Google CEO), Prith Banerjee (ANSYS CTO), Ion Stoica (Databricks Founder), Jared Kushner (former Senior Advisor to the President), David Patterson (Turing Award Winner), and Luis Videgaray (former Foreign and Finance Minister of Mexico).
  • If you're passionate about AI, physics, or the future of industrial innovation, we want to hear from you.
  • Can translate complex model decisions to customers and team
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This listing is sourced directly from UniversalAGI's careers page and normalized into a canonical job model.