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UniversalAGI

Deploys autonomous AI agents for enterprises

EMI Simulation Engineer

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

About the Job

Requirements

  • At least 4 years of hands-on, production experience running electromagnetic simulations for EMI/EMC and/or RCS analysis in industry or a defense/aerospace program setting.
  • Practical fluency with at least one major commercial full-wave electromagnetic solver, such as Ansys HFSS or SIwave, Dassault CST Studio Suite, Altair Feko, or Cadence Clarity, including simulation setup, meshing, and results validation.
  • Strong grounding in Maxwell's equations and electromagnetic theory as applied to real engineering problems.
  • Experience validating simulation results against measured or experimental data and understanding where simulation is and is not trustworthy.
  • Working proficiency in Python or a similar language for scripting, automating simulation pipelines, and structuring simulation output into clean, well-labeled datasets.
  • Ability to work across internal model-training needs and customer-facing analysis and translate clearly between them.
  • Ability to earn technical respect through hands-on contribution; comfort with an intense culture, significant ownership, ambiguity, rapid change, and multiple responsibilities; customer focus, deep-work orientation, high availability for critical issues, clear technical communication, continuous learning, accountability, and willingness to work extra hours when needed.

Responsibilities

  • Design and run EMI and RCS simulation campaigns using industry-standard electromagnetic solvers to generate high-fidelity training data for foundation models.
  • Build and maintain large, well-labeled, physics-accurate simulation datasets across a wide range of EMI and RCS geometries and scenarios, ensuring adequate coverage and quality for model training.
  • Produce simulation-derived EMI and RCS analyses and deliverables for customer engagements by translating customer requirements into simulation setups and validated results.
  • Validate simulation outputs against measured data and known analytical solutions to ensure datasets used for model training are physically trustworthy.
  • Automate and scale simulation pipelines, including scripting and batch-job orchestration, so data generation keeps pace with model-training needs.
  • Work directly with the AI research team to translate model-performance gaps into new simulation campaigns and help define the technical approach to electromagnetics in the foundation-model stack.

Desired Qualifications

  • Direct experience with radar systems, antenna arrays, or phased-array design, particularly in a defense or aerospace program context.
  • Experience with EMC compliance standards and design-stage compliance simulation, rather than only post-design test and fix.
  • Prior experience building or contributing to simulation datasets intended to train or validate machine-learning models.
  • Exposure to inverse-design, generative, or surrogate-modeling techniques applied to electromagnetics, such as machine-learning-based S-parameter prediction or geometry generation.
  • A PhD in electrical engineering, applied physics, or a related field; this is not required, as the role prioritizes hands-on industry experience over an academic research background.
  • Experience at a high-growth AI or engineering-software startup.

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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