About the role

WHO WE ARE AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com. We are looking for an experienced Senior Software Engineer who can design and build best-in-class behavior planning systems for autonomous driving in structured, low-speed environments. In this role, you'll own the design and implementation of key modules in the behavior planner — the decision-making layer that determines what the vehicle should do in complex, dynamic airside scenarios. You'll work at the intersection of mission-level goals and motion-level execution, tackling problems in multi-agent interaction modeling, rule-based and learned decision-making, and robust handling of edge cases unique to airport ground operations. This opportunity offers a deeply technical engineer the chance to shape a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our Planning Tech Lead and works closely with the autonomy engineering team. YOU WILL - Develop and implement advanced behavior planning algorithms for autonomous vehicles - Collaborate with cross-functional teams to ensure robust integration and functionality of planning systems - Design, write, and maintain efficient and scalable code in C++ and Python - Contribute to the architecture and continuous improvement of behavior planning software - Conduct extensive testing in simulated environments and real-world scenarios to validate and refine behavior planning algorithms - Analyze system performance and implement enhancements based on data and feedback - Maintain comprehensive documentation of code, algorithms, and system designs - Work closely with other engineering teams to ensure seamless coordination and development YOU HAVE - Proficient in modern C++ (11/14/17) and object-oriented programming - Skilled in Python for rapid prototyping and testing - Strong in debugging, profiling, and optimizing code - Deep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planning - Familiarity with path planning algorithms like A*, RRT, or optimization-based methods - Master’s degree in Computer Science, Robotics, or a related field - Minimum of 3 years of industry experience in autonomous driving, robotics, or a related field WE PREFER - Knowledge of state machines, behavior trees, and decision-making under uncertainty - Expertise in path planning algorithms such as A*, D*, and Rapidly-exploring Random Trees (RRT) - Knowledge of machine learning techniques, especially in the context of behavior prediction and planning - Experience with ROS / ROS2 - Implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environment - Ensuring that behavior planning algorithms can execute with minimal latency for real-time navigation - Proficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertainty - Master’s degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plus