Software Engineer, Robot Autonomy (Planning & Navigation)

About this role

Our Mission At Laelaps AI, we believe robotics is entering a transformative decade, much like the arrival of the internet. Advances in AI, cloud computing, and hardware are reshaping what autonomous systems can do. Our mission is to build the intelligent software that powers physical security in the real world - enabling robots and sensors to handle dangerous and critical tasks that humans shouldn't have to. By engineering the orchestration layer for intelligent security, we aim to create a world that is safer, more secure, and more resilient.

We're a strong founding team based in Zurich, backed by visionary investors and advisors. We are engineering the future of security today! THE ROLE As a Software Engineer on Robot Autonomy, you will make our robots navigate dependably across real customer sites. Our stack works. The gap between working and dependable is the whole job. Every new site tests how a robot understands its surroundings and chooses where to go: a ramp the planner avoids, a narrow passage that exposes a poor route, a gate that changes the map, a person who steps into the robot's path, or localization drift that builds over a long patrol.

You treat those cases as the real navigation problem to solve, not as edge cases. You'll shape the technical choices behind reliable navigation, from sensor selection, ground segmentation, and traversability estimation to predicting how people and vehicles move and planning safe, efficient routes around them. The system has to work day and night, in challenging weather, across different embodiments and changing site conditions.

We measure success by whether the robot completes its patrol on a live site, not by how it performs in simulation. WHAT YOU'LL WORK ON Navigation and path-planning design: how robots represent traversable space, select routes, avoid obstacles, and reach goals across complex sites. Sensor integration driven by navigation requirements, including what ground segmentation and traversability estimation need in day, night, and challenging weather.

Environment understanding: how the robot distinguishes ground from obstacles and estimates which terrain is safe and practical to traverse. Behavior prediction: anticipate how people, vehicles, and other dynamic obstacles will move, and plan routes that stay safe and efficient around them. Field reliability: reproduce failures from deployments, find the root cause, and fix it at the right layer, from sensor data and maps to costmaps, planners, and recovery behaviors.