Senior Staff Engineer, Autonomy Behaviors (R5363)

F7d8749a; Washington (District of Columbia); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Bonus

Benefits

Equity

Job summary

Shield AI seeks an experienced autonomy engineer to advance tactical autonomy algorithms for unmanned aircraft, blending traditional control with learning-based methods. You will work across perception, planning, simulation, hardware, and flight-test teams to deliver robust autonomy in diverse mission sets.

The role requires strong software development skills in C++/Python, familiarity with RTOS, and a background in robotics, motion planning, and multi-agent coordination, with eligibility to

Qualifications

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering or Aerospace Engineering or equivalent practical experience.
• Typically requires 10+ years with a Bachelor’s degree; 9+ with a Master’s; 7+ with a PhD or equivalent.
• Proficiency in C++ and Python; familiarity with RTOS.
• Significant robotics background: motion planning, behavior modeling, autonomous systems design.
• Experience with unmanned system technologies (air domain) and related algorithms.
• Experience with simulation tools such as AFSIM and NGTS for testing/validation.
• Ability to obtain a SECRET clearance.

Responsibilities

• Design tactical autonomy algorithms for unmanned aircraft across air/land/sea with minimal supervision.
• Develop high-performance software modules for planning, decision-making and behavior execution.
• Implement and test multi-agent coordination and target engagement behaviors.
• Integrate autonomy with ML approaches for robust, adaptive performance.
• Collaborate with perception, planning, simulation, hardware and flight-test teams.
• Deploy autonomy capabilities to real platforms and participate in field tests/demos.
• Analyze mission data to diagnose failures and drive iterative improvement.
• Contribute to autonomy roadmap through R&D and prototyping of new algorithms.

Skills

C++

Python

RTOS

Robotics

Motion planning

Education

BS in CS/EE/ME/AE or equivalent

MS in CS/EE/ME/AE or equivalent

PhD (plus)

Tools

AFSIM

NGTS

Simulation environments

Job description

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 https://shield.ai/. Follow Shield AI on LinkedIn https://www.linkedin.com/company/shield-ai, X https://x.com/shieldaitech, Instagram https://www.instagram.com/shield_ai, and YouTube https://www.youtube.com/@Shield_AI.

The Autonomy Capabilities Team develops functionality to automate single- and multi-agent teams of platforms in pursuit of mission objectives and acts as a central discipline-aligned focal-point for encouraging consistent usage of technical approaches across business portfolios. This team operates at all levels of the command-and-control hierarchy (from advanced control laws, through motion planning, and up to advanced tactical behaviors and multi-agent coordination) and across a multitude of mission sets, platform types, and operational domains (e.g., air, sea, space). The team puts a strong emphasis on both fundamentals (e.g., aircraft kinematics/dynamics, trajectory design, optimization, information fusion, efficient algorithms, etc.) and software integration skillsets (e.g. structures, protocols, threading, interface management, etc.) to bring market-differentiating capabilities to customers that seamlessly operate within their integration contexts. This position is perfect for an individual who enjoys solving complex problems across a diverse set of programs and integration contexts. An ideal candidate is expected to address operational system needs through a multitude of advanced methodologies that blend traditional control system approaches with advanced optimization. Developed solutions are expected to be integrated into real-world platforms with near-term program impacts and rewards and so balancing theory with practice and rigorous implementation is paramount.

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 #LI-ED1 #LE

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 fact