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Shield AI

Builds autonomous aircraft for defense

Manager of Engineering - Autonomous Pilot Integration

Engineering LeadershipUpdated on Nov 11
Full-timeWashington, DC, USA

About the Job

Requirements

  • A BS, MS, or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or a similar field, or equivalent practical experience.
  • Typically, at least 7 years of related experience with a Bachelor's degree, 5 years with a Master's degree, or 4 years with a PhD, or equivalent work experience.
  • At least 2 years of direct people-management experience, including running one-on-ones, performance reviews, and hiring decisions.
  • Demonstrated experience building or growing an engineering team, including interviewing, hiring, and onboarding engineers.
  • Track record of mentoring engineers and supporting their technical and career development.
  • Demonstrated experience leading a small technical team or owning a major capability from design through field delivery.
  • Experience authoring or negotiating interface contracts or Interface Control Documents with internal or external stakeholders.
  • Direct experience with launched effects, loitering munitions, expendable autonomous systems, or comparable small unmanned platforms.
  • Experience with multi-agent, swarm, or fleet-scale autonomy.
  • Strong 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 Data Distribution Service or message buses.
  • Hands-on experience supporting live exercises, customer demonstrations, or operational test events for launched effects or similar small unmanned 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

  • Manage a small-to-mid-sized engineering team, typically 3–8 engineers; own performance, growth, leveling, and delivery; and run one-on-ones, performance reviews, and team rituals.
  • Drive hiring for the area by identifying needed skills, partnering with recruiting, conducting interviews, setting hiring standards, and closing candidates.
  • Mentor engineers through technical problems, create stretch opportunities, provide actionable technical feedback, and support their development.
  • Develop and integrate autonomy software onto launched effects platforms, including payload computer bring-up, autopilot integration, multi-agent coordination, and fleet-scale deployment to disconnected or air-gapped environments; lead a small team through delivery of a major capability or program.
  • Lead a small feature crew or sub-program, set technical direction, break down work, unblock the team, and report progress to leadership and stakeholders.
  • Act as a primary technical interface with Autonomy Capabilities and Perception teams, feature crews, autopilot vendors, C2 providers, and customer or contractor partners; author and negotiate Interface Control Documents and interface contracts.
  • Drive design reviews, Interface Control Documents, and post-mortems, and improve rigor and close process gaps across teams.
  • Own the build, configuration, and validation process for mission-ready systems and fleet-scale deployments, often 50–150+ units in disconnected environments; coordinate hardware/software compatibility, mission readiness, and Capability Release cadence.
  • Travel to test sites and customer exercises to support live mission operations, including flight tests, range exercises, multi-agent live events, and customer demonstrations; 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 partner 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.
  • Own interface contracts with C2 providers and drive compliance with common message and open-systems standards, including UCI, OMS, MOSA, WOSA, and TAK/CoT.
  • Travel typically around 20–30% of the year to office locations, customer sites, range exercises, and integration events.

Desired Qualifications

  • Direct experience with PX4 or ArduPilot at the platform integration level.
  • Experience using and developing on QGroundControl or other Qt-based ground control stations.
  • Proficiency in Python for scripting, automation, and analysis.
  • Experience leading a feature crew, sub-program, or small team in an unmanned systems context.
  • Experience growing engineers from mid-level to senior individual contributor, or supporting promotion decisions through a leveling framework.
  • Experience with air-gapped, disconnected, or otherwise constrained deployment of autonomous systems at fleet scale.
  • Familiarity with tactical edge C2, such as TAK or CoT, and ground operator workflows.
  • Experience working with embedded contractor engineers, Federally Funded Research and Development Center partners, or customer-funded staff augmentation models.
  • Experience supporting international defense customer programs, including Foreign Military Sales or direct commercial sales.
  • Experience owning customer- or partner-facing technical relationships, such as with autopilot vendors, C2 providers, or government program offices.
  • Track record of cross-team improvements in processes, rigor, documentation, or developer experience.
  • Familiarity with autonomy stacks, motion planning, or vehicle-control integration.
  • Competence in avionics 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.
  • Proficiency in developing automation tools for system testing, logging, and data parsing.
  • Build-system experience, such as Conan or CMake, and familiarity with continuous integration and continuous delivery pipelines.
  • Comfort interfacing with Department of Defense stakeholders during field events or technical reviews.
  • Experience with common message and open-systems standards such as UCI, OMS, MOSA, or WOSA.

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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