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Shield AI

Builds autonomous aircraft for defense

Guidance – Navigation and Control Engineer

Flight Dynamics & GNCUpdated on Nov 11
Full-timeSeattle, WA, USAIn-person

About the Job

Requirements

  • Demonstrated hands-on experience designing, implementing, and flight-testing guidance laws for autonomous shipboard recovery, including recovery using relative navigation without GPS/GNSS.
  • Strong understanding of moving-platform guidance, ship-relative reference frames, deck motion, and terminal position, velocity, and attitude constraints.
  • Experience integrating guidance with relative-navigation systems and assessing the closed-loop effects of navigation bias, noise, latency, and dropouts.
  • Strong background in flight dynamics and guidance and control, including the relationship between guidance demands, aircraft tracking bandwidth, and available control authority.
  • Proficiency in C++ for real-time algorithm implementation and MATLAB/Simulink or Python for algorithm development and analysis.
  • Experience executing verification and validation through simulation, hardware integration, flight testing, and post-flight analysis.
  • Demonstrated ability to own a technical capability and resolve problems across subsystem boundaries while working effectively with navigation, controls, software, and test engineers.
  • Ability to obtain and maintain a U.S. security clearance.

Responsibilities

  • Design and implement ship-relative guidance for approach, station keeping, alignment, and terminal recovery.
  • Develop deck-motion compensation and landing-timing strategies that account for navigation uncertainty, aircraft response, control authority, and touchdown or capture constraints.
  • Work closely with state estimation and sensing teams to define relative-navigation requirements and ensure recovery guidance remains robust to measurement errors, latency, and intermittent sensor availability.
  • Implement recovery sequencing and contingency logic, including hold, wave-off, go-around, retry, and responses to degraded or lost navigation.
  • Develop and integrate real-time guidance software in C++, working with flight controls, autonomy, embedded software, and recovery-system teams.
  • Define recovery performance requirements and verify them through 6DOF simulation, Monte Carlo analysis, software-in-the-loop testing, and hardware-in-the-loop testing.
  • Support test planning, flight readiness assessments, and flight operations. Analyze test data, diagnose performance shortfalls, and drive improvements between tests.
  • Provide technical direction within the recovery-guidance effort, mentor engineers, and communicate design decisions, limitations, and test results across teams.

Desired Qualifications

  • Full-scale, at-sea flight-test experience with autonomous shipboard recovery.
  • VTOL or rotorcraft experience involving precision recovery to constrained or significantly moving landing platforms.
  • Experience characterizing recovery performance across ship motion, wind over deck, ship airwake, turbulence, and degraded visibility.
  • Experience integrating vision, infrared, lidar, radar, or cooperative RF sensing into a relative-navigation and recovery system.
  • Experience supporting ship–aircraft dynamic-interface testing, recovery-envelope development, flight safety, or airworthiness.
  • Familiarity with Linux-based development, Git, automated testing, and CI/CD workflows.
  • Ability to obtain S//SAR access.

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
Series H
Total funding
$4.8B
Headquarters
San Diego, CA
Founded
2015

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