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.
This position is perfect for an individual who enjoys solving the most complex problems across a portfolio of diverse domains and modalities. An ideal candidate is expected to apply classical autonomous techniques, algorithms, and theory to various platforms in multiple tactical scenarios. These solutions are expected to be integrated into real-world problems with near-term program impacts and rewards.
Shield AI is committed to developing cutting-edge autonomy for unmanned aircraft operating across all Department of Defense (DoD) domains, including air, sea, and land. We aim to push the envelope by combining traditional autonomous systems algorithms with deep reinforcement learning-based solutions to deliver unmatched capability, agility, and speed in deploying advanced technologies that support national defense
What you'll do:
Tactical Autonomy Design – Design tactical autonomy algorithms to enable unmanned aircraft to perform complex missions across air, land, and sea domains with minimal human supervision.
High-Performance Software Development – Develop high-performance software modules that incorporate planning, decision-making, and behavior execution strategies for dynamic and adversarial environments.
Behavior Architecture Implementation – Implement and test behavior architectures that enable multi-agent coordination, target engagement, reconnaissance, and survivability in contested scenarios.
Hybrid Autonomy Integration – Work at the intersection of classical autonomy and machine learning, blending rule-based systems with learning-based methods such as reinforcement learning to achieve robust, adaptive behavior.
Cross-Functional Collaboration – Collaborate with cross-functional teams including perception, planning, simulation, hardware, and flight test to ensure seamless integration of autonomy solutions on real-world platforms.
Deployment & Field Testing – Deploy autonomy capabilities to real platforms and participate in field tests and flight demos, validating performance in operationally relevant conditions.
Mission Data Analysis – Analyze mission logs and performance data to diagnose failures, optimize behavior models, and inform iterative development.
R&D and Roadmapping – Contribute to the autonomy roadmap by researching and prototyping new algorithms, identifying tactical capability gaps, and proposing novel solutions that advance Shield AI’s mission.
Program Support & Adaptation – Support defense-focused programs and customer needs by adapting autonomy solutions to evolving mission sets, compliance requirements, and operational feedback.
Travel Requirement – Members of this team typically travel around 10-15% of the year (to different office locations, customer sites, and flight integration events).
Required Qualifications:
BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
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.
Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS).
Significant background in robotics technologies related to motion planning, behavior modeling, decision-making, or autonomous system design.
Significant experience with unmanned system technologies and accompanying algorithms (specifically air domain)
Experience with simulation tools and environments (e.g., AFSIM, NGTS) for testing and validation.
Strong problem-solving skills, with the ability to troubleshoot and optimize system performance.
Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment.
Ability to obtain a SECRET clearance.
Preferred Qualifications:
Experience applying ML/RL techniques in autonomy pipelines.
Background in collaborative behaviors, swarm robotics, or distributed decision-making.
Familiarity with tactical behaviors for unmanned systems in DoD or government programs.
Work on behaviors applicable across air, ground, and maritime vehicles.
Hands-on experience supporting flight demos or live exercises.
Experience with UCI and OMS Standards
