Senior Software Engineer, Navigation

Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.

About The Role

Join the Autonomy team as a Senior Software Engineer focused on Navigation. You will be a core contributor, driving the design and deployment of real-time motion planning and navigation systems that empower our humanoid robots to operate robustly and autonomously in complex logistics and manufacturing environments. This is a high-impact role essential to scaling our commercial deployments, improving the efficiency of autonomous loco-manipulation behaviors, and achieving software readiness for the next generation robot platforms.

About The Work Design, implement, and deploy 3D motion planning algorithms for locomotion, with an emphasis on whole-body collision-aware motion execution in real-time. Own the core components of our navigation stack, specifically the local planning maps, terrain models, and grid map representations used for path and motion planning with collision avoidance. Advance our locomotion capabilities by developing and maintaining a 3D footstep path planner aiming to significantly reduce navigation cycle times.

Define and implement the necessary navigation features and route planning algorithms to enable coordinated movement and resource sharing within multi-agent robot fleets. Drive the maturity of our release processes by designing, implementing, and maintaining robust regression testing pipelines for motion planning and navigation modules. Collaborate with the AI and Controls teams to integrate locomotion behaviors with RL policies and support whole-body control.

, Gazebo, MuJoCo, Isaac Sim) to physical robots. About You 5+ years of professional experience in robotics, specifically developing and deploying real-time navigation and motion planning systems for autonomous mobile platforms (humanoids, quadrupeds, autonomous vehicles). , octomaps, voxel grids) for local path planning and collision avoidance.

Deep technical understanding of locomotion-specific path and motion planning algorithms, including sampling-based planners (RRT/PRM), optimization-based methods (MPC/LQR), and hybrid A*. Expert proficiency in modern C++ (C++17/20), with a proven track record of writing high-performance, multithreaded code for robotics applications. , Ceres, IPOPT, OSQP).

Proven ability to systematically test and debug systems on physical robots, and integrate perceived environment data (LiDAR, camera, depth sensing) into the planner.

Qualifications

Experience training and deploying Reinforcement Learning (RL) agents for complex locomotion behaviors. Hands-on experience implementing Model Predictive Control (MPC) or similar optimization-based control techniques for dynamic robot locomotion. Familiarity with perception pipelines and the integration of perceived environment data into the planning stack.

, NVBlox, specialized CUDA implementations) for high-throughput, low-latency map updates and querying. , EKF, particle filters). Experience with multi-robot coordination/route planning and abiding by boundary constraints in a workcell map.

Experience with multi-robot mapping and localization, including map persistence and sharing capabilities.