Responsibilities

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.
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.

Qualification

BS/MS in Computer ScienceDirect experience with launched effectsExperience with multi-agentStrong proficiency in C++Familiarity with middlewareProficiency in Python for scriptingExperience leading a feature crewExperience with air-gappedFamiliarity with tactical edge C2 (e

Required

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).

Preferred

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.

Manager of Engineering - Autonomous Pilot Integration (R5153) at f7d8749a-72d6-407c-bf98-292ea630c73a · LumiJobs

Manager of Engineering - Autonomous Pilot Integration (R5153)

Responsibilities

Qualification

Required

Preferred

Company

f7d8749a-72d6-407c-bf98-292ea630c73a

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