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UniversalAGI

Deploys autonomous AI agents for enterprises

Aerospace Simulation Engineer

AerodynamicsConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • At least 3 years of hands-on industry experience running aerospace computational fluid dynamics simulations, including preprocessing, simulation, post-processing, and design iteration.
  • Strong experience with Star-CCM+ and OpenFOAM as a primary solver.
  • Experience across subsonic, transonic, supersonic, and hypersonic flow regimes.
  • A solid background in heat transfer, thermal analysis and modeling, and conjugate heat transfer.
  • Deep understanding of fluid mechanics, compressible and incompressible flow, meshing, boundary conditions, and numerical methods.
  • Ability to communicate effectively across customers, engineering, and research teams.
  • Ability to execute and deliver at a strong pace.
  • Ability to work in a high-intensity, fast-paced startup environment with evolving priorities and tight deadlines.

Responsibilities

  • Design, preprocess, mesh, simulate, and post-process aerodynamics and thermal simulations for aerospace configurations at scale and speed.
  • Develop systematic approaches to designing, meshing, and simulating hundreds or thousands of configurations across flow regimes, and build data pipelines to train foundation models.
  • Guide product development and AI models for physics by working on research problems with the AI team and bridging traditional computational fluid dynamics with machine learning.
  • Work directly with clients to solve their problems and define benchmark datasets, validation criteria, and workflows to demonstrate model accuracy relative to traditional simulation.
  • Generate high-quality simulation data at scale to improve foundation models.
  • Advise the AI research team on compressible and incompressible flow, turbulence modeling across flow regimes, conjugate heat transfer, thermal analysis, shock interactions, and mesh design tradeoffs.
  • Lead technical customer conversations with customers and internal teams, translating between aerospace computational fluid dynamics and artificial intelligence.

Desired Qualifications

  • A master's degree or higher in Aerospace Engineering, Mechanical Engineering, or a closely related field.
  • Proficiency in programming languages such as Python or Java for simulation automation and data pipeline development.
  • Prior experience integrating artificial intelligence or machine learning models into simulation pipelines.
  • Industry experience in adjacent computational fluid dynamics domains such as automotive, defense, or energy.
  • Experience at high-growth AI startups from Seed to Series C.
  • Forward-deployed experience.

About the Company

UniversalAGI

Deploys autonomous AI agents for enterprises

UniversalAGI operates as a forward-deployed AI lab that builds and deploys autonomous AI agents for enterprises and government organizations. Its platform provides the infrastructure, talent, and security needed to turn business concepts into production-ready AI applications that work with an organization’s most sensitive data. The system includes a suite of agents and automation tools and can often convert a concept into a working app in under an hour using natural language inputs, with emphasis on security, scale, and adaptability. The company differentiates itself by embedding expert AI teams with clients to deliver mission-critical, production-grade AI—often in secure or air-gapped environments for sensitive national data—and by combining no-code capabilities with enterprise-grade AI transformations. UniversalAGI aims to enable rapid, secure AI adoption across both private and public sectors, delivering autonomous, reliable AI solutions for complex, data-sensitive challenges.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
San Francisco, CA
Founded
Not listed

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