Staff Engineer, Modelling and Simulation (R6248)

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube .

Job Description:

The Hivemind Simulation team provides the simulation capabilities that power the AI Factory’s training and evaluation for the next generation autonomous AI pilots. The Simulation Platform team builds the simulation framework and foundational infrastructure that allows engineers to bring together simulators, scale experiments, and confidently evaluate autonomy before flight. The team’s work enables simulation applications to build on a shared, performant, and extensible foundation. Our guiding principle is simple: autonomy should not know it is in a simulation.

As a Staff Software Engineer on the Simulation Platform team, you will shape how autonomous pilots are tested by building and integrating simulators and developing Monte Carlo infrastructure. Drawing on experience building and running real-time aircraft simulations, you will enable teams to evaluate autonomy, guidance, navigation, and control (GNC), and runtime assurance (RTA) systems at scale. This individual contributor role includes driving technical direction and mentoring engineers.

What you'll do:

• Grow the simulation framework’s ecosystem by integrating existing simulators and established standards, and by build new ones where needs are identified.
• Build reusable Monte Carlo infrastructure for parameterization, execution, reproducibility, and collection of results across large simulation campaigns.
• Develop multithreaded and multi-process simulation capabilities, addressing synchronization, timing, state exchange, and performance.
• Partner with autonomy, GNC, and RTA engineers as well as operators in the field to translate evaluation needs into simulation interfaces and infrastructure.
• Support platform specific performance validation using physics models (e.g, 6DoF, 3DoF, etc.).
• Set technical direction, lead design reviews, and mentor engineers in simulation architecture and production software development.

Required qualifications:

• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years with a Master’s degree; or 7 years with a PhD; or equivalent work experience.
• Strong proficiency in C++, with demonstrated experience designing, implementing, and maintaining production performance-critical software.
• Demonstrated experience building and running multithreaded/multiprocess real-time simulations involving aircraft dynamics.
• Experience both developing Monte Carlo infrastructure and using it to design, execute, and analyze simulation campaigns.
• Demonstrated ability to drive technical decisions, mentor engineers, and collaborate across software and domain engineering teams.
• Experience developing software/simulation under a defined V&V lifecycle

Preferred qualifications:

• Experience supporting airworthiness certification efforts, including developing simulation evidence for verification, validation, and safety assessment (e.g., DO-178C, MIL-HDBK-516C).
• Strong Python skills for simulation tooling, experiment automation, and analysis.
• Experience with distributed simulation and model interoperability standards such as HLA, DIS, and FMI/FMU.
• Experience with industry-standard simulation tools such as JSBSim, FlightGear, X-Plane, Gazebo, Isaac Sim, or Simulink, or equivalent environments.
• Experience with closed-loop autonomy simulation, including sensor inputs and interfaces between autonomy and the simulated environment.
• Experience with uncertainty modeling, statistical analysis, and scenario coverage for Monte Carlo evaluation.
• Testing / Operating Safety Critical Software (e.g., DO-178C)

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