Staff Engineer, Autonomy - Tactical Behaviors (r3914)

Shield AI Shield AI · Defense · Washington, DC +2 · Flight System Integration

Staff Engineer focused on designing and developing tactical autonomy algorithms for unmanned aircraft, integrating classical autonomy with reinforcement learning, and implementing behavior architectures for complex missions in dynamic environments. The role involves high-performance software development, cross-functional collaboration, and field testing.

What you'd actually do

  1. Design tactical autonomy algorithms to enable unmanned aircraft to perform complex missions across air, land, and sea domains with minimal human supervision.
  2. Develop high-performance software modules that incorporate planning, decision-making, and behavior execution strategies for dynamic and adversarial environments.
  3. Implement and test behavior architectures that enable multi-agent coordination, target engagement, reconnaissance, and survivability in contested scenarios.
  4. 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.
  5. Collaborate with cross-functional teams including perception, planning, simulation, hardware, and flight test to ensure seamless integration of autonomy solutions on real-world platforms.

Skills

Required

  • BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or equivalent practical experience
  • 7+ years of related experience with a Bachelor’s degree; or 5 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience
  • Proficiency in C++ and Python
  • 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
  • Ability to troubleshoot and optimize system performance
  • Excellent communication and teamwork skills
  • Ability to obtain a SECRET clearance

Nice to have

  • 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

What the JD emphasized

  • minimal human supervision
  • dynamic and adversarial environments
  • multi-agent coordination
  • contested scenarios
  • blending rule-based systems with learning-based methods such as reinforcement learning
  • robust, adaptive behavior
  • real-world platforms
  • operationally relevant conditions
  • mission logs and performance data
  • autonomy roadmap
  • novel solutions
  • defense-focused programs
  • customer needs
  • evolving mission sets
  • compliance requirements
  • operational feedback
  • C++ and Python
  • real-time operating systems (RTOS)
  • motion planning
  • behavior modeling
  • decision-making
  • autonomous system design
  • unmanned system technologies
  • simulation tools and environments
  • troubleshoot and optimize system performance
  • collaborative, multidisciplinary environment
  • SECRET clearance

Other signals

  • design tactical autonomy algorithms
  • develop high-performance software modules
  • implement and test behavior architectures
  • hybrid autonomy integration
  • deployment & field testing