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, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. 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 builds autonomy solutions for a wide range of CONOPs and mission sets. 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 an unmanned platform — air, maritime, space, or effects/expendables, depending on the program — then integrate, validate, and field it on the real hardware. In this role, you'll 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. You'll partner closely with the Autonomy Capabilities and Perception teams, feature crews, and external platform integrators (vehicle/autopilot control vendors, C2 providers). It's a hands-on role for engineers who like seeing their code operate in the real world — whether that's flying, sailing, orbiting, or downrange — and want to be there when it does.
At this level, you'll own the technical direction across multiple programs — driving the autonomy reference implementation and common patterns that portfolios adopt, anticipating where the autonomy stack needs to evolve, adapting as programs and priorities shift, and aligning with engineering leadership early. You'll serve as the subject-matter expert other teams seek out on hard, ambiguous problems in unknown solution spaces; mentor senior engineers and other team leads; drive cross-team improvements in rigor and process; and represent the team to engineering leadership, customer/program offices, and standards bodies.
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.
What You'll Do:
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Develop & Field Autonomy — Develop & integrate autonomy software solutions onto unmanned platforms (air, maritime, space, or effects/expendables), including payload computer bring-up, container-based deployment (e.g., k3s/k3d), and configuration across onboard compute, sensors, and command-and-control interfaces — and own the technical direction across a set of related programs, driving the autonomy reference implementation and common patterns that keep delivery coherent across portfolios.
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Technical Strategy & Leadership — Set the technical direction across multiple programs; drive the autonomy reference implementation and common patterns that portfolios adopt; anticipate where the stack needs to go and adapt as priorities shift; align with engineering leadership early and maintain outward status; serve as the subject-matter expert that the broader org reaches for when hard, ambiguous problems in unknown solution spaces land on the team.
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Collaboration & Cross-Engineering Influence — Build effective working relationships across engineering; represent the team to engineering leadership, customer/program offices, standards bodies, and external partners (platform integrators, vehicle/autopilot control vendors, C2 providers); shape architecture decisions beyond the team.
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Mentorship & Growth — Mentor senior engineers and other team leads; provide cross-functional mentorship to engineers in adjacent departments; help shape the leveling and career bar for the team and the broader engineering organization.
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Design & Documentation — Drive cross-functional design reviews, architecture documents, and post-mortems across many teams; publish content that informs decisions beyond the team; set the rigor and process bar for the broader engineering org.
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Pre-deployment Preparation — 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.
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On-site Test & Mission Support — Travel to test sites and support live mission operations (flight tests, range exercises, on-water trials, integration events), including safety checks, system bring-up, and troubleshooting under time-critical constraints.
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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.
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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.
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Continuous Improvement — Build tools and processes to improve integration timelines, test/mission reliability, and team efficiency across deployment cycles.
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C2 Interoperability & Standards — Set the strategy for C2 interoperability across our portfolio; shape interface evolution with internal and external stakeholders; own implementation and compliance against command-and-control standards (e.g., A-GRA, UCI, OMS).
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Hiring — Define the skills bar and hiring strategy for senior roles in your area; partner with managers on long-term staffing plans; assess candidates accurately and onboard new senior engineers.
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Travel Requirement – Members of this team typically travel around 10-20% of the year (to different office locations, customer sites, and integration/test events).
Required Qualifications:
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BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
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Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience.
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Proficiency in C++, with experience developing or integrating real-time or latency-sensitive systems.
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Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics.
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Familiarity with middleware, pub-sub, or IPC frameworks used in autonomy or robotics systems (e.g., DDS, message buses).
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Hands-on experience supporting demos, exercises, or field/mission tests for unmanned or autonomous systems.
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Experience with autonomy simulation environments for testing and validation.
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Demonstrated experience leading multiple teams or driving cross-program technical initiatives from concept through fielded delivery.
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Track record as the subject-matter expert sought across engineering on hard, ambiguous problems in unknown solution spaces in your discipline.
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Track record of setting forward-looking technical strategy and adjusting course as programs and priorities evolve.
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Track record of mentoring senior engineers and team leads, and shaping the career bar for the discipline.
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Experience shaping architecture decisions, interface contracts, and standards across multiple teams.
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Strong problem-solving skills, with the ability to troubleshoot and optimize system performance across the full stack.
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Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary
