Reporting directly to the Head of the Control Team, the Autonomous System Engineer will drive the development of GNSS-denied navigation, guidance, and terminal autonomy for unmanned aerial systems. This role is central to enabling reliable autonomous operations in contested and degraded environments, from perception-driven navigation to closed-loop terminal guidance.

• Design, develop, and validate navigation, guidance, and control (NGC) algorithms for autonomous drones, with a strong focus on GNSS-denied and degraded-signal environments.
  
  

• Develop and implement advanced control, state estimation, and sensor-fusion algorithms, including visual-inertial, inertial-only, or multi-sensor approaches.
  
  

• Implement autonomy and control software primarily in C++, leveraging the ROS 2 framework and applying test-driven development (TDD) and modern software engineering best practices.
  
  

• Architect, integrate, and maintain a cohesive ROS 2–based autonomy stack, combining multiple perception, navigation, and control packages into a reliable end-to-end autonomous system.
  
  

• Interface the autonomy stack with flight control systems via MAVLink, enabling robust command, telemetry, and state feedback between onboard autonomy and the autopilot.
  
  

• Deploy, optimize, and validate autonomy software on the NVIDIA Jetson platform, accounting for real-time constraints, hardware acceleration, and power limitations.
  
  

• Perform extensive simulation, bench testing, and flight testing, including debugging complex interactions between perception, navigation, and control layers.
  
  

• Produce and maintain high-quality technical documentation covering algorithms, software architecture, testing procedures, and system behavior.
  
  

• Collaborate closely with control, autopilot, AI, hardware, and systems engineering teams to ensure seamless system integration and mission readiness.
  

• Bachelor’s or Master’s degree in Robotics, Computer Science, Software Engineering, Aerospace Engineering, or a closely related discipline.
  

• 10–15 years of professional experience in autonomous systems, navigation, guidance, control, or robotics software development.

• Advanced proficiency in C/C++, with strong software design, debugging, and performance-optimization skills.

• Proven experience developing autonomy software using ROS 2, including node design, lifecycle management, and inter-process communication.

• Solid background in embedded systems, real-time constraints, and deployment on resource-constrained hardware.

• Hands-on experience integrating autonomy stacks with MAVLink-based autopilots.

• Strong understanding of navigation and control theory, including state estimation, sensor fusion, and closed-loop guidance.

• Experience deploying and optimizing software on NVIDIA Jetson platforms.

• Excellent problem-solving skills, autonomy, and the ability to operate effectively in a high-ownership, fast-moving startup environment.

• Strong communication and collaboration skills, with the ability to work across multidisciplinary teams.

Nice to Have

• Experience with PX4 or ArduPilot autopilot ecosystems.

• Background in GNSS-denied navigation, visual navigation, terrain-relative navigation, or terminal guidance systems.

• Familiarity with computer vision or perception-driven autonomy.

• Experience in defense, aerospace, or safety-critical autonomous systems.

• Prior involvement in flight testing and real-world deployment of autonomous drones.