Senior Engineer, Flight Controls - X-BAT (R4814)

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. Demonstrate