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:
In this role, you will contribute to the flight control system for XBAT, with responsibility for delivering stable, predictable, and operationally robust performance across all phases of flight, including vertical takeoff, hover, transition out-bound, wing-borne flight, transition in-bound, and precision recovery.
What you'll do:
Design and implement flight control laws and supporting logic across multiple flight regimes.
Build and mature high-fidelity 6DOF simulation environments used for control development and ensure accurate pre-flight performance predictions
Execute verification activities, including linear analysis, Monte Carlo campaigns, disturbance/sensitivity/degraded operation testing, and HIL validation
Diagnose and resolve simulation-to-test mismatches, including unidentified dynamics and modeling gaps
Support flight test operations and contribute to rapid iteration between flights
Work closely with propulsion, aero, actuation, sensors, state estimation, and autonomy teams to ensure accurate integrated system performance in the 6DOF simulation environment.
Required qualifications:
5+ years of experience in flight controls / GNC on real flight vehicles.
Experience performing one or more of the following technical flight control assignments:
Vehicle Modeling and Simulation:
Demonstrated experience implementing time-accurate mathematical models of the vehicle aerodynamics, mass properties, fuel system, propulsion system, sensors, actuators into a 6DOF simulation environment.
Control Law Design:
Demonstrated experience designing inner and outer loop control laws for fixed-wing aircraft using classical or modern control techniques.
Control Allocation:
Demonstrated experience designing control allocation algorithms for over-actuated systems handling actuator saturation, rate limits, failures and degradation.
Guidance and Autonomy Integration:
Demonstrated experience designing and testing real-time trajectory generation algorithms.
Verification and Validation:
Demonstrated experience executing linear, nonlinear, and Monte Carlo Analyses in a 6DOF simulation environment.
Demonstrated experience executing sensitivity studies, worst-case disturbance analysis, and/or failure detection and accommodation studies validating control robustness against requirements.
Demonstrated experience characterizing aircraft flying qualities against tailored MIL-HDBK-516 Section 6 requirements within a high-fidelity 6DOF Simulation framework.
Demonstrated experience in generating flight control and simulation data artifacts for Airworthiness Certification (Simulation Description Document, Flying Qualities Report).
Flight Test Support:
Demonstrated experience in test planning, envelope expansion strategy, and test point selection.
Post-Flight Analysis:
Demonstrated experience analyzing flight data, comparing predicted vs actual behavior, performing system identification and model refinement tasks, and implementing control design or simulation model updates.
Strong background in aircraft flight dynamics and 6DOF simulation
Proficiency in C++, MATLAB/Simulink, and/or Python.
Ability to obtain and maintain a U.S. security clearance
Ability to obtain a S//SAR level security clearance desired.
Preferred qualifications:
Autonomous systems or missile/UAV GNC background
Familiarity with:
Sensor and air data systems
CI/CD pipelines and modern DevSecOps practices
Experience integrating NPSS propulsion models (transient and steady state) into a 6DOF simulation environment.
Experience with HIL or integrated simulation/test environments and Linux-based development workflows (Git, etc.)
Experience operating in rapid development environments with tight iteration loops between simulation and test
