Build and lead simulation platform infrastructure for autonomous aircraft systems. Responsibilities include integrating and developing simulators, creating scalable Monte Carlo experimentation capabilities, implementing multithreaded and multiprocess real-time simulations, validating physics models, partnering with autonomy and GNC teams, and guiding architecture, design reviews, and engineering mentorship.
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.
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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Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
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