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AeroVect is a Series A autonomous vehicle company transforming ground handling operations for airlines and ground service providers globally. We are seeking an experienced Senior Software Engineer to design and build behavior planning systems for autonomous vehicles operating in structured, low-speed airport environments.
In this role, you will own the design and implementation of key modules in the behavior planner—the decision-making layer that determines vehicle actions in complex, dynamic airside scenarios. You'll work at the intersection of mission-level goals and motion-level execution, tackling multi-agent interaction modeling, rule-based and learned decision-making, and edge case handling unique to airport ground operations. This is a deeply technical position that shapes a market-defining enterprise product combining autonomous vehicle technology with a robotics-as-a-service business model. You will report to the Planning Tech Lead and collaborate closely with the autonomy engineering team.
Key responsibilities include developing and implementing advanced behavior planning algorithms for autonomous vehicles; collaborating with cross-functional teams on robust integration; designing, writing, and maintaining efficient, scalable code in C++ and Python; contributing to architecture and continuous improvement of behavior planning software; conducting extensive testing in simulated and real-world scenarios; analyzing system performance and implementing enhancements; maintaining comprehensive documentation; and ensuring seamless coordination with other engineering teams.
REQUIREMENTS:
- Proficient in modern C++ (11/14/17) and object-oriented programming
- Skilled in Python for rapid prototyping and testing
- Strong debugging, profiling, and code optimization capabilities
- Deep understanding of behavior planning algorithms (state machines, behavior trees, probabilistic planning)
- Familiarity with path planning algorithms (A*, RRT, optimization-based methods)
- Master's degree in Computer Science, Robotics, or related field
- Minimum 3 years of industry experience in autonomous driving, robotics, or related field
PREFERRED:
- Knowledge of state machines, behavior trees, and decision-making under uncertainty
- Expertise in path planning algorithms (A*, D*, RRT)
- Machine learning techniques for behavior prediction and planning
- ROS/ROS2 experience
- High-frequency re-planning systems for dynamic environment adaptation
- Low-latency behavior planning for real-time navigation
- Optimization techniques and probabilistic models for planning under uncertainty
- PhD in Robotics, AI, Mathematics, or related field with focus on planning, optimization, or control theory
