Senior Software Engineer, Behavior Planning

About the Company

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day‑to‑day operations. It is a Series A company backed by top‑tier venture capital investors in aviation and autonomous driving. Customers include some of the world’s largest airlines and ground handling providers. More information is available at www.aerovect.com.

About the Role

The Senior Software Engineer will design and build best‑in‑class behavior planning systems for autonomous driving in structured, low‑speed environments. Reporting to the Planning Tech Lead, the engineer 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. The role works closely with the autonomy engineering team and offers the chance to shape a market‑defining enterprise product that combines autonomous vehicle technology with a robotics‑as‑a‑service (RaaS) business model.

Responsibilities

• 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.

Qualifications

• Proficient in modern C++ (C++11/14/17) and object‑oriented programming.
• Skilled in Python for rapid prototyping and testing.
• Strong debugging, profiling, and code‑optimization abilities.
• 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.

Preferred Qualifications

• 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).
• Experience with machine‑learning techniques for behavior prediction and planning.
• Familiarity with ROS / ROS2.
• Experience implementing systems that can re‑plan at high frequencies to adapt to dynamic environmental changes.
• Ability to ensure behavior‑planning algorithms execute with minimal latency for real‑time navigation.
• Proficiency in optimization techniques and probabilistic models for 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 (a plus).

Compensation

Salary range: $180,000 – $220,000.