Senior Engineer, Autonomy - Tactical Behaviors (r4235)

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

Senior Engineer focused on designing and implementing tactical autonomy algorithms for unmanned aircraft, blending classical techniques with reinforcement learning for complex missions in defense applications. Responsibilities include software development, behavior architecture implementation, hybrid autonomy integration, 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, and/or similar degree, or equivalent practical experience
  • minimum of 5 years of related experience with a Bachelor’s degree; or 4 years and a Master’s degree; or 2 years with a PhD; or equivalent work experience.
  • Proficiency in programming languages such as 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 work effectively in a collaborative, multidisciplinary environment.
  • 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

  • complex missions across air, land, and sea domains
  • dynamic and adversarial environments
  • multi-agent coordination
  • contested scenarios
  • classical autonomy and machine learning
  • reinforcement learning
  • real-world platforms
  • field tests and flight demos
  • operationally relevant conditions
  • mission logs and performance data
  • autonomy roadmap
  • new algorithms
  • tactical capability gaps
  • novel solutions
  • defense-focused programs
  • customer needs
  • evolving mission sets
  • compliance requirements
  • operational feedback
  • unmanned system technologies and accompanying algorithms (specifically air domain)
  • simulation tools and environments
  • troubleshoot and optimize system performance
  • collaborative, multidisciplinary environment
  • obtain a SECRET clearance

Other signals

  • develop high-performance software modules
  • implement and test behavior architectures
  • work at the intersection of classical autonomy and machine learning
  • deploy autonomy capabilities to real platforms
  • analyze mission logs and performance data