Manager of Engineering - Autonomous Pilot Integration (R5153)

Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

The Autonomous Pilot Integration team for launched effects builds autonomy solutions for small, often air- or ground-launched platforms that operate in multi-agent fleets and frequently in disconnected or air-gapped environments. We combine capabilities from the Autonomy Capabilities team (motion planning, tactics), the Perception team (e.g., track fusion), and the HivemindSDK to develop the autonomy software that runs on launched effects platforms, then integrate, validate, and field it on the real hardware — for U.S. and international defense customers. Our engineers write new autonomy code — such as mission behaviors, platform-specific control, multi-agent coordination, contingencies, and executive autonomy — and own it end-to-end from software-in-the-loop, to hardware-in-the-loop, to vehicle-in-the-loop, to live test exercise.

In this role, you'll lead a team of autonomy engineers working on launched effects programs — owning their delivery, their growth, and the technical health of your area. A core part of the job is growing the team: hiring strong engineers, mentoring them through hard technical work, and shaping their career development. You'll stay technically active — close enough to the code and the integration work to make sound technical decisions, to be credible to your team, and to lead them through the design, development, and delivery of a major capability or program. You'll partner closely with the Autonomy Capabilities and Perception teams, feature crews, autopilot vendors (e.g., PX4, ArduPilot), C2 providers, and customer/contractor partners that staff and operate alongside our team. This portfolio runs at a fast cadence — frequent Capability Release milestones, multi-agent fleet operations, air-gapped deployments at scale, and demanding live exercises — and you'll set the pace for your team accordingly.

Shield AI is committed to developing cutting-edge autonomy for unmanned platforms across every operating domain — air, maritime, space, and effects/expendables — in service of the U.S. Department of Defense and our international defense customers. Our Autonomous Pilot Integration engineers bridge the gap between R&D and deployment, ensuring autonomous systems function reliably and effectively wherever and whenever they're needed most. 

Lead the Team — Manage a small-to-mid-sized engineering team (typically 3–8 engineers); own performance, growth, leveling, and delivery; run 1:1s, performance reviews, and team rituals.

Grow the Team via Hiring — Drive hiring for your area: identify the skills you need, partner with recruiting, run interviews, set the bar, and personally close strong candidates.

Grow Engineers Technically — Mentor engineers through hard problems; create stretch opportunities; give direct, actionable technical feedback; help engineers level up in both skill and impact.

Develop & Field Autonomy — Develop & integrate autonomy software solutions onto launched effects platforms, including payload computer bring-up, autopilot integration (e.g., PX4, ArduPilot), multi-agent coordination, and fleet-scale deployment to disconnected or air-gapped environments — and lead a small team through the design, development, and delivery of a major capability or program.

Technical Leadership — Lead a small feature crew or sub-program; set technical direction, break down work, unblock the team, and report progress to leadership and stakeholders.

Collaboration Across Teams & Partners — Act as a primary technical interface with the Autonomy Capabilities team (motion planning, tactics), the Perception team, feature crews, autopilot vendors (e.g., PX4, ArduPilot), C2 providers, and customer/contractor partners (including embedded contractor engineers and U.S. or international government program offices); author and negotiate ICDs and interface contracts rather than just consume them.

Design & Documentation — Drive design reviews, ICDs, and post-mortems for your area; push the team toward higher rigor and close process gaps that span teams.

Pre-deployment Preparation — 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 (CR) cadence with capability and feature teams.

On-site Test & Mission Support — Travel to test sites and customer exercises to support live mission operations (flight tests, range exercises, multi-agent live events, customer demonstrations), including safety checks, system bring-up, and troubleshooting under time-critical constraints.

Hardware/Software Debugging — Diagnose and resolve integration issues across complex autonomy stacks, payload computers, and embedded systems in lab and field environments — including memory, CPU, and timing profiling under operationally-representative loads.

Mission Data & Debrief Support — Capture mission and test data, reproduce issues in simulation, and partner with autonomy capability owners to drive fixes back into the next build.

Continuous Improvement — Build tools and processes to improve integration timelines, test/mission reliability, and team efficiency across deployment cycles.

C2 Interoperability & Standards — Own the interface contracts with C2 providers and drive compliance against common message and open-systems standards (e.g., UCI, OMS, MOSA, WOSA, TAK/CoT).

Travel Requirement – Members of this team typically travel around 20-30% of the year (to different office locations, customer sites, range exercises, and integration events).

BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience

Typically requires a minimum of 7 years of related experience with a Bachelor's degree; or 5 years and a Master's degree; or 4 years with a PhD; or equivalent work experience.

2+ years of direct people-management experience (running 1:1s, performance reviews, hiring decisions, growth planning).

Demonstrated experience building or growing an engineering team — including interviewing, hiring, and onboarding new engineers.

Track record of mentoring engineers and growing their technical skill and career trajectory.

Demonstrated experience leading a small technical team or owning a major capability from design through field delivery.

Experience authoring or negotiating interface contracts / ICDs 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 working with embedded systems, shell scripting, and system diagnostics.

Familiarity with middleware, pub-sub, or IPC frameworks used in autonomy or robotics systems (e.g., DDS, 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.

Strong problem-solving skills, with the ability to troubleshoot and optimize system performance across the full stack.

Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment.

Ability to obtain a SECRET clearance.

Direct experience with PX4 and/or ArduPilot at the platform integration level.

Experience using and developing on QGroundControl (QGC) 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 into senior IC, 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 (e.g., TAK, CoT) and ground operator workflows.

Experience working with embedded contractor engineers, FFRDC partners, or customer-funded staff augmentation models.

Experience supporting international defense customer programs (FMS or direct commercial sales).

Experience owning customer- or partner-facing technical relationships (e.g., autopilot vendors, C2 providers, government program offices).

Track record of cross-team improvements (process, 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 (e.g., k3s, k3d, Docker) on embedded or payload compute.

Proficiency in developing automation tools for system testing, logging, and data parsing.

Build-system experience (e.g., Conan, CMake) and CI/CD pipeline familiarity.

Comfortable interfacing with DoD stakeholders during field events or technical reviews.

Experience with common message and open-systems standards such as UCI, OMS, MOSA, or WOSA.

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Full-time regular employee offer package:

Pay within range listed + Bonus + Benefits + Equity

 

Temporary employee offer package:

Pay within range listed above + temporary benefits package (applicable after 60 days of employment)

 

Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.

 

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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.