Senior Staff Engineer, Autonomy Behaviors (R4073)

United States·WashingtonFull Time Employeesenior

OtherStaff Engineer

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Overview

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.

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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.

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

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).

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.

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

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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.