Shield AI
Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices and facilities across the U.S., Europe, the Middle East, and the 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.
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.
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.
Collaboration Across Teams — Work closely with the Autonomy Capabilities team (motion planning, tactics), the Perception team, feature crews, and external partners (platform integrators, vehicle/autopilot control vendors, C2 providers) to deliver and validate mission-critical functionality on time.
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.
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.
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 — Implement and validate compliance with command-and-control standards (e.g., A-GRA, UCI, OMS) and coordinate with C2 providers on interface contracts and integration milestones.
Travel Requirement – Members of this team typically travel around 10-20% of the year (to different office locations, customer sites, and integration/test 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 5 years of related experience with a Bachelor’s degree; or 4 years and a Master’s degree; or 2 years with a PhD; or equivalent work experience.
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, ActiveMQ).
Hands-on experience supporting demos, exercises, or field/mission tests for unmanned or autonomous 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 supporting uncrewed systems (air, maritime, space, ground, or effects/expendables) or similar field test campaigns.
Proficiency in Python for scripting, automation, and analysis.
Familiarity with autonomy stacks, motion planning, or vehicle-control integration.
Competence in vehicle electronics bring-up (avionics, spacecraft buses, or vessel control), payload computer integration, or hardware-in-the-loop debugging.
Experience with container orchestration (e.g., k3s, k3d, Docker) on embedded or payload compute.
Familiarity with platform control / autopilot stacks (e.g., PX4, ArduPilot, spacecraft flight software, vessel autopilots).
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 C2 standards such as A-GRA, UCI, or OMS.
Familiarity with government-furnished simulation environments (e.g., AFSIM, NGTS) is a plus.
$160,000 - $240,000 a year
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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.
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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.