Principal GNC Engineer

Job description

Job responsibilities

• Own the end-to-end GNC architecture and technical roadmap across all mission phases, from launch or takeoff through terminal operations, recovery, or landing.
• Translate mission objectives and vehicle concepts into GNC requirements, interfaces, performance budgets, and verification criteria.
• Design, analyze, and mature guidance algorithms, control laws, state-estimation solutions, gain schedules, and control-allocation strategies.
• Ensure robust performance across the full operating envelope while accounting for aerodynamic uncertainty, actuator limits, sensor errors, latency, structural modes, environmental disturbances, and off-nominal…
• Lead flight-dynamics modeling, system identification, Monte Carlo analysis, and model correlation using CFD, wind-tunnel, ground-test, and flight-test data.
• Establish and maintain rigorous software-in-the-loop, and hardware-in-the-loop verification workflows.
• Drive production implementation of flight-critical algorithms in embedded, real-time software; review code, numerics, timing, and fault-handling behavior.
• Define flight-readiness criteria and lead GNC activities for test planning, safety reviews, range execution, data analysis, anomaly resolution, and rapid iteration.

Job requirements

• Bachelor’s degree in aerospace engineering, mechanical engineering, electrical engineering, robotics, physics, mathematics, or a related technical field.
• Significant experience designing, implementing, and testing GNC systems for aircraft, missiles, launch vehicles, spacecraft, high-performance UAVs, or comparable autonomous systems, typically gained through 10 or more…
• Demonstrated ownership of a GNC system through multiple phases of the development lifecycle, including requirements, analysis, implementation, verification, integration, and flight test.
• Deep knowledge of flight dynamics, stability and control, classical and modern control theory, state estimation, trajectory generation, and system identification.
• Experience developing robust algorithms for nonlinear systems with real-world actuator, sensor, computational, and timing constraints.
• Proficiency with MATLAB/Simulink for modeling and analysis, plus C or modern C++ for production or embedded implementations.
• Experience with Monte Carlo analysis, uncertainty quantification, requirements-based verification, and SIL/HIL test environments.
• Strong understanding of flight-test practices, telemetry analysis, controller tuning, anomaly investigation, and risk-managed test progression.