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 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.br/br/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.br/br/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.br/br/You Willbr/br/Develop and implement advanced behavior planning algorithms for autonomous vehiclesbr/br/Collaborate with cross-functional teams to ensure robust integration and functionality of planning systemsbr/br/Design, write, and maintain efficient and scalable code in C++ and Pythonbr/br/Contribute to the architecture and continuous improvement of behavior planning softwarebr/br/Conduct extensive testing in simulated environments and real-world scenarios to validate and refine behavior planning algorithmsbr/br/Analyze system performance and implement enhancements based on data and feedbackbr/br/Maintain comprehensive documentation of code, algorithms, and system designsbr/br/Work closely with other engineering teams to ensure seamless coordination and developmentbr/br/You Havebr/br/Proficient in modern C++ (11/14/17) and object-oriented programmingbr/br/Skilled in Python for rapid prototyping and testingbr/br/Strong in debugging, profiling, and optimizing codebr/br/Deep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planningbr/br/Familiarity with path planning algorithms like A*, RRT, or optimization-based methodsbr/br/Master's degree in Computer Science, Robotics, or a related fieldbr/br/Minimum of 3 years of industry experience in autonomous driving, robotics, or a related fieldbr/br/We Preferbr/br/Knowledge of state machines, behavior trees, and decision-making under uncertaintybr/br/Expertise in path planning algorithms such as A*, D*, and Rapidly-exploring Random Trees (RRT)br/br/Knowledge of machine learning techniques, especially in the context of behavior prediction and planningbr/br/Experience with ROS / ROS2br/br/Implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environmentbr/br/Ensuring that behavior planning algorithms can execute with minimal latency for real-time navigationbr/br/Proficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertaintybr/br/Master's degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plusbr/br/#J-18808-Ljbffr