Senior Staff Engineer, Autonomy - Tactical Behaviors (r4073)

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

Senior Staff Engineer focused on designing and developing tactical autonomy algorithms for unmanned aircraft, integrating classical autonomous techniques with reinforcement learning for complex missions in defense applications.

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, 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.

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

  • Ability to obtain a SECRET clearance.

Other signals

  • Develop high-performance software modules that incorporate planning, decision-making, and behavior execution strategies for dynamic and adversarial environments.
  • Implement and test behavior architectures that enable multi-agent coordination, target engagement, reconnaissance, and survivability in contested scenarios.
  • 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.