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Shield AI

Builds autonomous aircraft for defense

Engineer – Autonomous Systems Integration

AvionicsUpdated on Nov 11
Full-timeSan Diego, CA, USAIn-person

About the Job

Requirements

  • The candidate must have 10 or more years of experience in UxS or UAS systems integration, robotics hardware integration, autonomy test operations, flight test, field engineering, embedded systems, or similar hands-on technical roles.
  • The candidate must have demonstrated experience leading complex integration efforts across hardware, software, autonomy, networking, communications, sensors, and operational test environments.
  • The candidate must have practical experience bringing up, configuring, operating, and troubleshooting unmanned systems, onboard compute, flight controllers, radios, sensors, ground stations, and supporting test equipment.
  • The candidate must have working knowledge of Linux, embedded systems, networking, system configuration, data collection, logs, services, and field diagnostics.
  • The candidate must have experience with unmanned-systems autopilot or flight-control ecosystems such as PX4, ArduPilot, MAVLink, Pixhawk/Cube-class flight controllers, QGroundControl, Mission Planner, or equivalent systems.
  • The candidate must have experience supporting testing across simulation, hardware-in-the-loop, live-vehicle, field, or flight-test environments.
  • The candidate must be able to develop and communicate test plans, readiness criteria, operating assumptions, technical recommendations, and post-test findings for cross-functional audiences.
  • The candidate must have analytical, problem-solving, and debugging skills across ambiguous, cross-disciplinary technical issues.
  • The candidate must be able to lead through influence across engineering, test, product, operations, field, and customer-facing teams.
  • The candidate must be familiar with scripting, automation, or data-analysis workflows using Python, Bash, MATLAB, or similar tools.
  • The candidate must demonstrate ownership, urgency, and judgment in fast-moving environments where requirements, platforms, and constraints may evolve quickly.
  • The candidate must be able to comply with export-control, safety, security, customer-site, and mission-specific operating requirements.
  • The candidate must be able to obtain and maintain a Secret security clearance, and must be a U.S. citizen.

Responsibilities

  • Serve as a senior technical focal point for Hivemind integration and test readiness across unmanned aircraft, robotic systems, representative test vehicles, onboard compute, radios, sensors, payloads, and supporting ground equipment.
  • Lead hands-on integration and troubleshooting efforts spanning autonomy software, hardware, flight controllers, communications systems, networking, operator interfaces, and field operations.
  • Partner with engineering, test, product, operations, field, and customer-facing teams to evaluate new platforms and determine how they can best support Hivemind development, validation, training, demonstrations, and customer objectives.
  • Help take systems from early concept or benchtop integration through representative test, field execution, and operationally relevant demonstrations.
  • Provide senior-level technical judgment on platform suitability, integration complexity, test readiness, risk, safety, maintainability, cost, availability, and customer value.
  • Support test planning and execution across simulated, hardware-in-the-loop, live-vehicle, and flight-test environments while keeping the role focused on practical system readiness and evidence quality.
  • Help define clear readiness criteria, test expectations, operating assumptions, and handoff points for representative hardware used by Hivemind teams.
  • Diagnose complex cross-disciplinary issues and help route them effectively across software, autonomy, hardware, flight-test, networking, and operations stakeholders.
  • Contribute to test methods, metrics, and evidence practices that improve confidence in Hivemind behavior across representative and real-world environments.
  • Support automation, tooling, and data-review practices that improve repeatability, reduce manual burden, and make hardware-based testing easier to operate at scale.
  • Capture and share practical knowledge from platform bring-up, test events, flight operations, and customer-facing demonstrations so teams can reuse lessons learned.
  • Mentor engineers and operators on systems integration, hardware readiness, field troubleshooting, test discipline, and practical autonomy test execution.

Desired Qualifications

  • Experience with Hivemind, autonomy SDKs, autonomous aircraft systems, robotics middleware, simulation infrastructure, or edge-deployed autonomy software.
  • Hands-on experience with NVIDIA Jetson, embedded Linux, systemd services, containerized deployment, device provisioning, and field update workflows.
  • Experience with RF/radio setup, mesh networking, tactical datalinks, software-defined radios, or communications-degraded test scenarios.
  • Experience supporting flight test, range operations, customer trials, operational rehearsals, or complex demonstrations.
  • Experience integrating EO/IR cameras, gimbals, lidar, GPS/GNSS, IMUs, payloads, or perception sensors.
  • Experience contributing to test automation, regression frameworks, data validation, performance benchmarking, or CI/CD-integrated test workflows.
  • Familiarity with C++ for debugging, interface review, or collaboration with software engineering teams.
  • FAA Part 107, private pilot license, military UAS, aviation maintenance, flight-test, or range-safety experience.
  • Experience defining reference configurations, hardware baselines, supported configurations, or setup guidance for internal and external users.
  • Active Secret clearance or higher.

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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