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Shield AI

Builds autonomous aircraft for defense

Senior Software Engineer - Autonomous Pilot Integration, Weapons

Embedded EngineeringUpdated on Nov 14
Full-timeArlington County, Arlington, VA, USA

About the Job

Requirements

  • A Bachelor of Science or Master of Science in Computer Science, Electrical Engineering, Aerospace Engineering, Mechanical Engineering, or equivalent practical experience is required.
  • Typically, 5 or more years of relevant experience, or equivalent advanced-degree experience, is required.
  • Strong proficiency in C++ and experience developing or integrating real-time or embedded systems are required.
  • Experience with Linux-based development and embedded systems is required.
  • Experience integrating complex software and hardware systems is required.
  • Experience supporting system integration, testing, or field events is required.
  • The ability to obtain a Secret clearance is required.

Responsibilities

  • Develop and integrate autonomy software solutions onto launched effects platforms, including payload computer bring-up, autopilot integration, multi-agent coordination, and deployment to disconnected or air-gapped environments.
  • Own major features from software-in-the-loop through live flight testing and operational deployment.
  • Own major features or subsystems, drive technical execution, contribute to design decisions, mentor teammates, and help deliver complex autonomy capabilities.
  • Partner with the Autonomy Capabilities and Perception teams, feature crews, autopilot vendors, C2 providers, and customer or contractor partners to deliver integrated autonomy capabilities.
  • Contribute to design reviews, interface control documents, integration planning, and post-mortems, and help improve engineering rigor and cross-team execution.
  • Build, configure, and validate mission-ready systems for Capability Releases and fleet-scale deployments; coordinate hardware and software compatibility, mission readiness, and release readiness across engineering teams.
  • Travel to test sites, customer exercises, and live demonstrations to support flight operations, system bring-up, troubleshooting, and mission execution under operational timelines.
  • Diagnose and resolve integration issues across autonomy software, payload computers, embedded systems, and platform interfaces using simulation, laboratory testing, and operational data.
  • Capture mission and test data, reproduce issues in simulation, and partner with autonomy capability owners to drive improvements into future releases.
  • Develop tools and processes that improve integration timelines, testing reliability, deployment efficiency, and mission readiness.
  • Implement and validate interfaces with C2 providers while supporting compliance with common message and open-systems standards, including UCI, OMS, MOSA, WOSA, and TAK/CoT.
  • Travel approximately 10–20% of the year to office locations, customer sites, operator training events, flight tests, and integration exercises.

Desired Qualifications

  • Experience with launched effects, unmanned systems, or autonomous platforms is preferred.
  • Experience with PX4, ArduPilot, or comparable autopilot stacks is preferred.
  • Experience with multi-agent autonomy is preferred.
  • Python, Docker, CMake or Conan, or CI/CD experience is preferred.
  • Experience supporting military field exercises or defense customers is preferred.

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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