Senior Software Engineer - Behavior Planning

About AeroVect

AeroVect is revolutionizing ground handling operations globally by integrating autonomous technology to enhance daily workflows for airlines and ground service providers. Supported by top-tier venture capital firms in aviation and autonomous driving sectors, AeroVect’s clientele includes some of the largest airlines and ground handling companies in the world.

Role Overview

We seek an experienced Senior Software Engineer to design and develop state-of-the-art behavior planning systems for autonomous driving within structured, low-speed environments like airports.

This role requires ownership of core behavior planner modules — the decision-making layer responsible for defining vehicle actions in complex, dynamic airside conditions. The engineer will work at the confluence of mission-level objectives and motion-level execution, addressing challenges in multi-agent interaction modeling, rule-based and machine-learned decision processes, and robust handling of unique edge cases in airport ground operations.

This position offers an opportunity for a technically deep engineer to contribute to a leading-edge enterprise product melding autonomous vehicle technology with a robotics-as-a-service model. Reporting to the Planning Tech Lead and collaborating closely with the autonomy engineering team.

Primary Responsibilities

• Develop and implement advanced algorithms for behavior planning of autonomous vehicles
• Work collaboratively with cross-disciplinary teams to ensure integration and reliable operation of planning systems
• Produce, maintain, and optimize efficient and scalable codebases primarily in C++ and Python
• Influence architecture and drive continuous improvements in behavior planning software
• Conduct thorough testing using both simulations and real-world conditions to validate and enhance behavior algorithms
• Analyze system behavior and implement improvements based on empirical data and feedback
• Create and maintain detailed documentation covering code, algorithms, and system architecture
• Coordinate closely with other engineering groups to ensure harmonized development efforts

Essential Requirements

• Expertise in modern C++ standards (C++11/14/17) and sound object-oriented programming principles
• Proficiency in Python for rapid development, prototyping, and testing
• Strong skills in debugging, profiling, and performance optimization of complex code
• In-depth knowledge of behavior planning methods including state machines, behavior trees, and probabilistic approaches
• Familiarity with path planning techniques such as A*, Rapidly-exploring Random Trees (RRT), and optimization-based strategies
• Master’s degree in Computer Science, Robotics, or related disciplines
• A minimum of three years of relevant professional experience in autonomous driving, robotics, or similar fields

Preferred Qualifications

• Deep understanding of decision-making frameworks under uncertainty, including state machines and behavior trees
• Advanced experience with path planning algorithms like A*, D*, and RRT
• Knowledge of machine learning approaches related to behavior prediction and planning
• Experience working with Robot Operating System (ROS/ROS2)
• Developing systems capable of high-frequency re-planning responsive to dynamic environment changes
• Ensuring planning algorithms run with minimal latency to support real-time navigation
• Familiarity with optimization methods and probabilistic modeling for informed decision-making in uncertain conditions
• Advanced academic credentials (Master’s or PhD) focused on Robotics, AI, Mathematics, planning, optimization, or control theory are advantageous