Senior Software Engineer: Autonomous Behavior Planning

AeroVect; Dublin; On-site; EUR 90,000 - 120,000; Full time

Job summary

AeroVect is seeking a Senior Software Engineer to design and implement behavior planning modules for autonomous ground operations. You will integrate decision-making and motion execution in complex airside scenarios, shaping a market-defining enterprise product for RaaS.

You will work with the autonomy team, report to Planning Tech Lead, and contribute to multi-agent planning, learning-based decisions, and edge-case handling in low-speed environments.

Qualifications

• Master's degree in Computer Science, Robotics, or related field.
• Minimum 3 years of industry experience in autonomous driving, robotics, or related field.
• Proficient in modern C++ (11/14/17) and Python.

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.

Skills

C++ (modern)

Python

Debugging & profiling

Behavior planning

State machines

Behavior trees

Path planning

ROS/ROS2

Code optimization

Education

Master's degree in CS/Robotics

Tools

Job description

AeroVect is seeking a Senior Software Engineer to design and implement behavior planning modules for autonomous ground operations. You will integrate decision-making and motion execution in complex airside scenarios, shaping a market-defining enterprise product for RaaS.

You will work with the autonomy team, report to Planning Tech Lead, and contribute to multi-agent planning, learning-based decisions, and edge-case handling in low-speed environments.