Senior Software Engineer, Behavior Planning

AeroVect Inc.

Job Overview

Location

Remote

Job Type

Full-time

Full Job Description

📋 Description

• Senior Software Engineer, Behavior Planning role at AeroVect Inc., a Series A company transforming ground handling with autonomy for airlines and ground service providers worldwide.
• Design and implement key modules in the behavior planner — the decision-making layer that determines vehicle actions in complex, dynamic airside scenarios at the intersection of mission-level goals and motion-level execution.
• Work with a well-funded, innovative team backed by top-tier venture capital in aviation and autonomous driving, serving major airlines and ground handling providers globally.
• Shape a market-defining enterprise product combining autonomous vehicle technology with a robotics-as-a-service (RaaS) business model, reporting to the Planning Tech Lead and collaborating closely with the autonomy engineering team.
• Develop and implement advanced behavior planning algorithms for autonomous vehicles in structured, low-speed environments.
• 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 and real-world environments to validate and refine 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.
• Required: Proficiency in modern C++ (11/14/17) and object-oriented programming, skilled in Python for prototyping and testing, strong debugging, profiling, and optimization skills.
• Required: Deep understanding of behavior planning algorithms (state machines, behavior trees, probabilistic planning), familiarity with path planning (A*, RRT, optimization-based methods).
• Required: Master’s degree in Computer Science, Robotics, or related field; minimum 3 years industry experience in autonomous driving, robotics, or related field.
• Preferred: Knowledge of machine learning for behavior prediction, experience with ROS/ROS2, expertise in high-frequency re-planning, low-latency execution, optimization techniques, and probabilistic models under uncertainty.
• Preferred: Master’s or PhD in Robotics, AI, Mathematics, or related field with focus on planning, optimization, or control theory.

🎯 Requirements

• Proficiency in modern C++ (11/14/17) and object-oriented programming
• Skilled in Python for rapid prototyping and testing
• 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

🏖️ Benefits

• Opportunity to shape a market-defining enterprise product combining autonomous vehicle technology with robotics-as-a-service (RaaS)
• Work with a well-funded Series A company backed by top-tier venture capital in aviation and autonomous driving
• Collaborate with global customers including some of the world’s largest airlines and ground handling providers
• Remote work flexibility
• Engage in deeply technical work at the intersection of mission-level goals and motion-level execution
• Contribute to architecture and continuous improvement of behavior planning software in a collaborative engineering environment

Skills & Technologies

Python

Senior

Remote

Degree Required

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AeroVect Inc.

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About AeroVect Inc.

AeroVect Inc. builds autonomous ground vehicles and management software for airport cargo and baggage handling. Its electric tractors and tow-tugs automate loading, unloading, and transport of luggage and freight on tarmacs and in terminals, integrating with existing baggage systems and aircraft operations. The company combines AI perception, path planning, and fleet orchestration to reduce delays, labor costs, and emissions while improving ramp safety and throughput for airlines and ground-handling partners.

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