AI Product Engineer

📍 San Francisco | 🏢 5 Days Onsite

Location: Onsite in San Francisco

Compensation: Competitive Salary + Equity

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).

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.

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• • 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.

   

“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.