Sr. Autonomy Engineer – Swarm & Collaborative Planning

Zone 5 Technologies is redefining what's possible in unmanned aircraft systems by developing cutting-edge autonomous solutions. The Senior Autonomy Engineer will architect and deploy real-time multi-agent coordination, path planning, and collision avoidance systems for networked unmanned aerial swarms operating in complex environments.

Responsibilities:

• Design and implement distributed consensus algorithms and task allocation frameworks for agent swarms
• Develop robust path planning algorithms (RRT*, A*, optimization-based) that handle swarm formations, dynamic obstacles, no-fly and keep-in zones, and in-mission re-planning
• Develop optimized swarm search algorithms with decentralized decision making
• Build collision avoidance systems using geometric, optimization, and potential-field methods
• Create adaptive mission execution frameworks that respond to perception updates, communication dropouts, and adversarial conditions
• Design bandwidth-efficient coordination protocols that maintain swarm cohesion under severely constrained radio links
• Implement autonomy stacks in ROS2 with C++ for deterministic performance on embedded compute
• Develop Simulink models for algorithm validation and hardware-in-the-loop testing
• Optimize computational performance to meet real-time constraints on resource-limited platforms
• Architect communication-aware planning strategies that balance information sharing with bandwidth limitations
• Define system architecture for networked collaborative autonomy with degraded communications
• Write technical specifications and design documents for autonomy capabilities
• Collaborate with perception, controls, radio systems, and flight test teams to integrate and validate solutions

Requirements:

• Bachelor's in Computer Science, Robotics, Aerospace Engineering, Applied Mathematics, or related field (Master's preferred) – equivalent industry experience also welcome
• 5-7+ years of experience developing autonomous systems with focus on multi-agent coordination or motion planning
• Expert proficiency in C++ for real-time robotics/aerospace applications
• Strong hands-on experience with ROS2 architecture, nodes, and distributed systems
• Demonstrated expertise with Simulink for control and planning algorithm development
• Deep knowledge of path planning algorithms: sampling-based (RRT*, PRM), search-based (A*, D*), and optimization-based (MPC, trajectory optimization)
• Experience implementing collision avoidance and constraint satisfaction in multi-agent systems
• Solid understanding of distributed algorithms, consensus protocols, and network-aware planning
• Proven ability to integrate perception inputs (object tracks, maps, terrain) into planning decisions
• Experience designing systems for bandwidth-constrained or intermittent network communications
• Experience with swarm robotics, formation control, or multi-robot task allocation
• Knowledge of communication-constrained planning and decision-making under uncertainty
• Familiarity with radio communication protocols, message serialization, and data compression techniques
• Understanding of tactical data links, MAVLink, or other UAV communication standards
• Background in networked control systems or event-triggered communication strategies
• Familiarity with aerial platform dynamics and UAV autopilots (PX4, ArduPilot)
• Background in optimal control, game theory, or distributed optimization
• Experience with GNSS-denied navigation or contested environment operations
• Experience in motion planning, multi-agent systems, or autonomous systems