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Shield AI

Builds autonomous aircraft for defense

Guidance, Navigation, and Control Engineer

Flight Dynamics & GNCUpdated on Nov 14
Full-timeSeattle, WA, USAIn-person

About the Job

Requirements

  • At least 10 years of experience in flight controls, guidance, navigation, and control, or autonomous aircraft development, with technical ownership of flight-vehicle systems from requirements and design through integration and flight test.
  • Experience building or leading engineering teams, including establishing technical direction, assigning ownership, mentoring engineers, and delivering complex development efforts through coordinated team execution.
  • Experience owning technical roadmaps and project execution, including work scoping, effort estimation, staffing plans, milestone definition, dependency management, and technical risk reduction.
  • Deep expertise in aircraft flight dynamics, classical and modern control theory, nonlinear systems, and fixed-wing control law design, including stability, performance, and robustness across the operating envelope.
  • Experience developing or validating high-fidelity six-degree-of-freedom simulations and using ground- and flight-test data to identify modeling limitations, characterize uncertainty, and improve predictive capability.
  • Experience defining and executing requirements-based verification strategies, including linear and nonlinear analysis, Monte Carlo studies, integrated testing, and flight-test analysis.
  • Experience integrating guidance, control, and flight-mode logic, with an understanding of the division between flight autonomy and mission autonomy and the interfaces needed for feasible vehicle-level execution.
  • Proficiency in C++, including implementing, reviewing, and debugging guidance and control or simulation software and addressing real-time execution constraints.
  • Experience using MATLAB and/or Python for engineering analysis and verification.
  • Technical judgment and communication skills to resolve ambiguous cross-disciplinary problems and communicate decisions, assumptions, risks, and limitations to engineers and program leadership.

Responsibilities

  • Build and lead the Ranger guidance and control team; define staffing needs, establish technical ownership, and develop the team through mentorship, design reviews, and hands-on problem solving.
  • Own the guidance and control development roadmap by translating program objectives into phased plans for requirements development, algorithm maturation, simulation capabilities, software integration, verification, and flight testing; establish measurable milestones and align priorities with program leadership and partner teams.
  • Own project execution and delivery by scoping and estimating work, allocating resources, managing schedules and cross-team dependencies, and tracking progress against deliverables; identify technical and schedule risks, drive mitigation plans, and communicate trade-offs and resource needs.
  • Define and deliver the guidance and control architecture, including Auto-Taxi and automatic takeoff and landing algorithms, inner- and outer-loop control laws, guidance, trajectory validation, flight-mode logic, and control allocation; maintain stable, predictable aircraft performance through actuator constraints, disturbances, uncertainty, and defined degraded conditions.
  • Lead integration between flight autonomy and mission autonomy through A-GRA-aligned interfaces; establish responsibilities for mission-level decision-making and vehicle-level execution, including command validation, flight-mode transitions, status reporting, and contingency coordination.
  • Lead development and validation of high-fidelity six-degree-of-freedom simulation capabilities; establish model fidelity requirements, validation plans, and uncertainty bounds to support control development, vehicle-level trades, and credible pre-flight performance predictions.
  • Own the guidance and control verification strategy and supporting compliance evidence; define requirements-based acceptance criteria and verification coverage across linear and nonlinear analysis, Monte Carlo campaigns, sensitivity and failure studies, and software- and hardware-in-the-loop testing.
  • Drive cross-disciplinary trades with propulsion, aerodynamics, actuation, state estimation, embedded software, and autonomy teams; translate guidance and control performance needs into subsystem requirements and resolve interface, timing, and integration issues.
  • Lead guidance and control preparation and analysis for ground and flight testing, including test-point selection, envelope-expansion planning, pre-flight predictions, and post-flight reconstruction; provide evidence-based flight-readiness recommendations, resolve simulation-to-test discrepancies, and drive verified corrective changes.

Desired Qualifications

  • Experience leading development, integration, or flight verification of autonomous fixed-wing aircraft.
  • Direct experience defining, implementing, or verifying A-GRA-aligned interfaces, or integrating flight autonomy with a separate mission-autonomy provider.
  • Experience building a guidance and control team or development capability for a new aircraft program, including establishing technical practices, simulation infrastructure, verification workflows, and development plans.
  • Experience applying flight safety and airworthiness processes, deriving flight control requirements, and producing supporting artifacts such as simulation descriptions, verification reports, and flying-qualities analyses.
  • Experience evaluating navigation errors, air data uncertainty, altitude-sensing limitations, latency, and data validity against flight control and automatic takeoff and landing performance requirements.
  • Experience establishing software- and hardware-in-the-loop capabilities, automated regression testing, and continuous integration and continuous delivery workflows using Linux, Git, and modern C++ development practices.
  • Experience integrating steady-state or transient NPSS propulsion models or model outputs into a six-degree-of-freedom simulation environment.
  • Experience leading guidance and control execution in developmental flight-test programs, balancing rapid iteration with configuration control, verification rigor, and disciplined flight-readiness assessments.

About the Company

Shield AI

Builds autonomous aircraft for defense

Shield AI builds autonomous aircraft and flight software for military and allied defense customers, with a focus on operations where conventional remote control breaks down. Its Hivemind AI pilot handles decisions during a mission, while the V-BAT aircraft gathers intelligence and locates targets. Aircraft makers use its software tools to develop and test their own autonomy, and its Aechelon business supplies visual and sensor simulation for pilot training. The company earns money from aircraft sales, autonomy software and contracted engineering and operational services. Shield AI was founded in 2015 and is headquartered in San Diego, California.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$4.8B
Headquarters
San Diego, CA
Founded
2015

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