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Shield AI

Builds autonomous aircraft for defense

Staff Software Engineer - Autonomous Pilot Integration

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

About the Job

Requirements

  • A bachelor's or master's degree in a relevant engineering discipline, or equivalent practical experience.
  • Typically, 7 or more years of relevant experience.
  • Expert-level C++ and Linux development experience.
  • Experience leading complex autonomy or embedded software integration efforts.
  • Experience influencing technical direction across multiple engineering teams.
  • Experience supporting operational test events or customer deployments.
  • Ability to obtain a Secret clearance.

Responsibilities

  • Lead technical execution of major autonomy capabilities, drive technical direction, coordinate cross-functional execution, mentor engineers, and help deliver complex integration efforts.
  • Develop and integrate autonomy software solutions onto launched effects platforms, including autopilot integration, payload systems, executive autonomy, multi-agent coordination, and fleet-scale deployment to disconnected or air-gapped environments.
  • Serve as a primary technical interface with the Autonomy Capabilities team, Perception team, feature crews, autopilot vendors, command-and-control providers, and customer and contractor partners; influence interface definitions and coordinate integration across organizations.
  • Lead design reviews, contribute to architecture decisions and interface control documents, improve engineering rigor, and establish repeatable integration practices across multiple efforts.
  • Drive mission readiness for Capability Releases and fleet-scale deployments by coordinating validation, release planning, hardware/software compatibility, and operational readiness.
  • Provide technical leadership during flight tests, customer demonstrations, range exercises, and operational deployments while troubleshooting complex issues under time-critical constraints.
  • Lead root-cause analysis across autonomy software, payload computers, embedded systems, networking, and platform interfaces using simulation, lab testing, and field data.
  • Analyze mission data, reproduce issues, coordinate corrective actions across engineering teams, and drive continuous improvements into future releases.
  • Build tools, automation, and engineering processes that improve deployment velocity, mission reliability, developer productivity, and integration efficiency.
  • Drive implementation of command-and-control interfaces and support compliance with open-systems standards while coordinating closely with external integration partners.
  • Travel typically 10–20% of the year to office locations, customer sites, operator training events, flight tests, and integration exercises.

Desired Qualifications

  • Experience with launched effects or distributed autonomous systems.
  • Experience integrating PX4, ArduPilot, or custom autopilot solutions.
  • Experience with fleet-scale autonomous operations.
  • Experience with disconnected or air-gapped deployments.
  • Experience mentoring engineers and leading technical initiatives.
  • Experience with UCI, OMS, MOSA, WOSA, or TAK/CoT.

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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