AI Product Engineer

Reposted One Month Ago
San Francisco, CA, USA
In-Office
Mid level
Artificial Intelligence • Information Technology • Automation
The Role
Own and ship the end-to-end platform for engineering customers to train and host physics models. Build frontend, backend, databases, cloud integrations, reusable templates, and UX; iterate on feedback; ensure reliability and scalability in production while collaborating closely with the CEO and founding team.
Summary Generated by Built In

📍 San Francisco | 🏢 5 Days Onsite

Location: Onsite in San Francisco

Compensation: Competitive Salary + Equity

 

Who We Are

Engineering simulation is one of the last major categories of software that AI hasn't rebuilt. The tools used to design aircraft, ships, reservoirs, and medical devices still run on numerical methods that are decades old, and an engineer can wait a full day for a single answer. UniversalAGI is building foundation models that learn physics directly from data, and they are already running in early deployments on real computational fluid dynamics and reservoir engineering problems for some of the largest industrial and defense organizations in the world.

We are a team of 25 researchers and engineers in San Francisco 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).

 

About the Role

UniversalAGI is hiring a Product Engineer to own and extend our customer-facing product across the stack. You will join a team of 25 researchers, engineers, and domain experts supporting early deployments in computational fluid dynamics and oil and gas reservoir engineering.

You will build the product experience through which engineers import CAD and 3D geometry, simulation and test data, and operating conditions; configure model workflows; monitor simulations and model jobs; compare predictions against trusted benchmarks; and deploy or export results.

This role owns the customer-facing product layer, including user workflows, interfaces, APIs, data models, visualization, and integrations. You will partner with platform engineering on the underlying ML execution infrastructure and with researchers who own model architectures and scientific methods.

You’ll work directly with the CEO, founding team, and customers to turn advanced research into reliable, repeatable engineering workflows.

 

What You'll Do

  • Own Customer Workflows: Build the end-to-end product experience from geometry and engineering data through model configuration, benchmarked predictions, and deployed or exported results.

  • Ship Across the Stack: Develop production features using React, TypeScript, Next.js, Python, databases, cloud services, and APIs.

  • Design Clear Product Abstractions: Create intuitive interfaces, workflow templates, and APIs for simulations, datasets, model jobs, evaluations, uncertainty, and engineering outputs.

  • Work Directly with Customers: Understand real engineering processes, identify recurring needs, and turn customer-specific lessons into scalable product capabilities.

  • Own Production Quality: Improve observability, performance, versioning, migrations, compatibility, and incident diagnosis across the customer-facing product.

  • Shape Product and Architecture: Partner with the founding team, Research, and Platform Engineering to define priorities, interfaces, and technical direction.

 

Qualifications

  • End-to-End Product Engineering: Experience shipping and operating customer-facing products across React/TypeScript frontends, Python backends, APIs, and data systems.

  • Product Judgment: Ability to turn complex technical workflows into clear, effective experiences for expert users.

  • Production Ownership: Comfortable designing maintainable systems, debugging production issues, and managing reliability, rollouts, and migrations.

  • Customer Focus: Able to work directly with technical users, make sound tradeoffs, and own outcomes in an early-stage environment.

 

Bonus Qualifications

  • Experience building ML-backed products, developer tools, or complex B2B software.

  • Experience with 3D or scientific visualization, WebGL, CAD, or CAE.

  • Experience with enterprise authentication or customer-controlled deployments.

  • Early-stage or zero-to-one product experience.

 

Cultural Fit

  • 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 cool tech

  • Deep Work: Values long, uninterrupted periods of focused work over meetings

  • High Availability: Ready to be deeply involved whenever critical issues arise

  • Communication: Can translate complex technical concepts to customers and team

  • Growth Mindset: Embraces the compounding returns of intelligence and continuous learning

  • Startup Mindset: Comfortable with ambiguity, rapid change, and wearing multiple hats

  • Work Ethic: Willing to put in the extra hours when needed to hit critical milestones

  • Team Player: Collaborative approach with low ego and high accountability

 

What We Offer

  • Opportunity to shape the technical foundation of a rapidly growing foundational AI company.

  • Work on cutting-edge industrial AI problems with immediate real-world impact.

  • Direct collaboration with the founder & CEO and ability to influence company strategy

  • Competitive compensation with significant equity upside.

  • In-person first culture - 5 days a week in office with a team that values face-to-face collaboration.

  • Access to world-class investors and advisors in the AI space.

 

Benefits

 

We provide great benefits, including:

  • Competitive compensation and equity.

  • Competitive health, dental, vision benefits paid by the company.

  • 401(k) plan offering.

  • Flexible vacation.

  • Team Building & Fun Activities.

  • Great scope, ownership and impact.

  • AI tools stipend.

  • Monthly commute stipend.

  • Monthly wellness / fitness stipend.

  • Daily office lunch & dinner covered by the company.

  • Immigration support.

 

How We’re Different

 

The credit belongs to the man who is actually in the arena, whose face is marred by dust and sweat and blood; who strives valiantly; who errs, who comes short again and again... who at the best knows in the end the triumph of high achievement, and who at the worst, if he fails, at least fails while daring greatly." - Teddy Roosevelt

 

At our core, we believe in being “in the arena.” We are builders, problem solvers, and risk-takers who show up every day ready to put in the work: to sweat, to struggle, and to push past our limits. We know that real progress comes with missteps, iteration, and resilience. We embrace that journey fully knowing that daring greatly is the only way to create something truly meaningful.

 

If you're ready to join the future of physics simulation, push creative boundaries, and deliver impact, UniversalAGI is the place for you.

Skills Required

  • Proven track record shipping customer-facing products with deep ownership over frontend, backend, and database layers
  • Strong software engineering fundamentals and clean componentized architectures
  • Deep technical comfort with Python on the backend
  • Experience with React, TypeScript, and Next.js on the frontend
  • Comfortable navigating databases and cloud APIs
  • Ability to hold the user journey while evaluating complex technical tradeoffs (product instinct)
  • Hands-on experience integrating AI components into customer products (LLMs, agents, ML features)
  • Experience with 3D applications, CAD, physics simulations, or engineering tooling domains
  • Prior early-stage startup experience (0 to 1 product development)
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The Company
HQ: San Francisco, California
4 Employees
Year Founded: 2025

What We Do

UniversalAGI is automating physical systems engineering across the entire product lifecycle with artificial intelligence.

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