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UniversalAGI

Deploys autonomous AI agents for enterprises

Reservoir Simulation Engineer

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

About the Job

Requirements

  • 3–5+ years of hands-on industry experience building and running reservoir simulation models for conventional and unconventional reservoirs, from model construction through history matching, forecasting, and field-development optimization.
  • Expertise in reservoir simulation frameworks such as Eclipse/Intersect, CMG, or OPM Flow, including blackoil and compositional formulations.
  • Deep understanding of reservoir engineering fundamentals, including PVT behavior, relative permeability, capillary pressure, well modeling, material balance, and history matching.
  • Understanding of the static-to-dynamic model handoff, including geologic and geocellular model construction, upscaling, and grid generation.
  • Ability to communicate effectively across customers, engineering teams, and research teams.
  • Ability to work in a high-intensity startup environment with evolving priorities and tight deadlines.
  • Ability to be deeply involved when critical issues arise and to work extra hours when needed to meet critical milestones.

Responsibilities

  • Design, build, and run blackoil and compositional reservoir simulation studies across conventional and unconventional reservoirs at large scale and speed.
  • Develop methods to construct reservoir models and systematically simulate hundreds or thousands of model variants, while building data pipelines to train foundation models.
  • Guide product and AI model development by working on research problems with the AI team and connecting traditional reservoir simulation with machine learning.
  • Work directly with clients to solve problems and define benchmark datasets, validation criteria, and workflows to evaluate model accuracy against traditional reservoir simulation.
  • Generate high-quality simulation data at scale to improve foundation models.
  • Advise the AI research team on PVT behavior and fluid characterization, relative permeability and capillary pressure, history matching and uncertainty quantification, multi-stage hydraulic fracturing and complex fracture networks, and production-decline behavior in unconventional reservoirs.
  • Lead technical customer conversations with customers and internal teams, translating between reservoir engineering and AI.

Desired Qualifications

  • Working proficiency in Python or a similar language for scripting, automating simulation pipelines, and structuring simulation output into clean, well-labeled datasets.
  • Experience integrating AI/ML models into reservoir workflows or generating simulation datasets for machine-learning model training or validation.
  • Experience with probabilistic or ensemble history matching, uncertainty quantification, or geostatistical modeling such as Gaussian processes or kriging.
  • Experience modeling unconventional reservoirs, including multi-stage hydraulic fracturing, complex fracture networks, and production-decline behavior distinct from conventional plays.
  • Master's or PhD in Petroleum Engineering, Reservoir Engineering, Geology, or a related field.
  • Domain expertise in geothermal or other subsurface-flow applications adjacent to oil and gas.
  • Experience at high-growth AI startups from Seed to Series C.
  • Forward-deployed experience working directly with customers to solve challenging problems.
  • Ability to earn technical respect through hands-on contribution.
  • Thriving in an intense work culture and prioritizing customer problems.
  • Preference for long, uninterrupted periods of focused work over meetings.
  • Ability to translate complex technical concepts to customers and the team.
  • Comfort with ambiguity, rapid change, and varied responsibilities.
  • Collaborative approach with accountability.

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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