S

Shield AI

Builds autonomous aircraft for defense

Senior Software Engineer - Autonomous Pilot Integration

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

About the Job

Requirements

  • A BS or MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or a similar field, or equivalent practical experience.
  • Typically, at least 5 years of related experience with a Bachelor's degree, 4 years with a Master's degree, 2 years with a PhD, or equivalent work experience.
  • Proficiency in C++, with experience developing or integrating real-time or latency-sensitive systems.
  • Proficiency in Linux-based development and experience with embedded systems, shell scripting, and system diagnostics.
  • Familiarity with middleware, publish-subscribe, or inter-process communication frameworks used in autonomy or robotics systems, such as DDS or ActiveMQ.
  • Hands-on experience supporting demonstrations, exercises, or field/mission tests for unmanned or autonomous systems.
  • Experience with autonomy simulation environments for testing and validation.
  • Ability to troubleshoot and optimize system performance across the full stack.
  • Ability to obtain a Secret clearance.

Responsibilities

  • Develop and integrate autonomy software onto unmanned platforms, including payload computer bring-up, container-based deployment, and configuration across onboard compute, sensors, and command-and-control interfaces.
  • Collaborate with the Autonomy Capabilities and Perception teams, feature crews, and external partners to deliver and validate mission-critical functionality.
  • Own the build, configuration, and validation process for mission-ready systems; coordinate hardware/software compatibility, mission readiness, and release cadence with capability and feature teams.
  • Travel to test sites and support live mission operations, including flight tests, range exercises, on-water trials, and integration events; perform safety checks, system bring-up, and troubleshooting under time-critical constraints.
  • Diagnose and resolve integration issues across autonomy stacks, payload computers, and embedded systems in lab and field environments, including memory, CPU, and timing profiling under operationally representative loads.
  • Capture mission and test data, reproduce issues in simulation, and work with autonomy capability owners to drive fixes into subsequent builds.
  • Build tools and processes to improve integration timelines, test and mission reliability, and team efficiency across deployment cycles.
  • Implement and validate compliance with command-and-control standards, including A-GRA, UCI, and OMS, and coordinate interface contracts and integration milestones with command-and-control providers.
  • Travel around 10–20% of the year to office locations, customer sites, and integration/test events.

Desired Qualifications

  • Direct experience supporting uncrewed systems or similar field-test campaigns.
  • Proficiency in Python for scripting, automation, and analysis.
  • Familiarity with autonomy stacks, motion planning, or vehicle-control integration.
  • Competence in vehicle electronics bring-up, payload computer integration, or hardware-in-the-loop debugging.
  • Experience with container orchestration, such as k3s, k3d, or Docker, on embedded or payload compute.
  • Familiarity with platform control or autopilot stacks, such as PX4, ArduPilot, spacecraft flight software, or vessel autopilots.
  • Proficiency in developing automation tools for system testing, logging, and data parsing.
  • Build-system experience, such as Conan or CMake, and familiarity with CI/CD pipelines.
  • Comfort interfacing with Department of Defense stakeholders during field events or technical reviews.
  • Experience with command-and-control standards such as A-GRA, UCI, or OMS.
  • Familiarity with government-furnished simulation environments, such as AFSIM or NGTS.

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

Recently Posted Jobs

Explore more opportunities at Shield AI

See more jobs