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AeroVect

Staff Software Engineer, Motion Planning

Posted Yesterday
In-Office or Remote
Hiring Remotely in London, Greater London, England, GBR
Senior level
In-Office or Remote
Hiring Remotely in London, Greater London, England, GBR
Senior level
Design and build production-grade mission, behavior, and motion planning systems for autonomous ground support vehicles in airport environments. Responsibilities include selecting planning algorithms, defining software architecture, optimizing trajectories, handling uncertainty, collaborating with perception and controls teams, promoting functional safety practices, and mentoring engineers. The role requires strong C++ or Python skills, Linux experience, autonomous systems planning expertise, and the ability to independently solve complex technical problems.
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Who We Are

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.

Job Description

We are looking for an experienced Staff Software Engineer who can design and build best-in-class planning systems for autonomous driving in structured, low-speed environments.

In this role, you'll be the technical backbone of the planning stack — owning the design and implementation of production-grade mission planning, behavior planning, and motion planning software. You'll work across the full planning pipeline to achieve category-defining vehicle autonomy for the airside, tackling hard problems in trajectory optimization, decision-making under uncertainty, and real-time constraint optimization.

This opportunity offers a deeply technical engineer the chance to shape a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our Planning Tech Lead and works closely with the autonomy engineering team.

You Will:

  • Design, implement, and iterate on the mission planner, behavior planner, and motion planner for autonomous ground support equipment operating in airport airside environments.

  • Drive key technical decisions across the planning stack — selecting algorithms, defining interfaces, and establishing the architecture that the team builds on.

  • Prototype and evaluate new planning approaches (e.g., optimization-based methods, search-based planners, learning-augmented pipelines) and bring the best ideas to production.

  • Collaborate cross-functionally with perception, controls, localization, and systems engineering teams to deliver an integrated autonomous driving system.

  • Establish and promote best practices in software development, functional safety, and systems engineering as they apply to the planning domain.

  • Mentor other engineers through technical guidance, code review, and design discussions.

You Have:

  • Bachelor's or Master's degree in Computer Science, Math, Electrical Engineering, Mechanical Engineering, Robotics, Physics, or a related field.

  • Extensive hands-on experience designing and implementing planning modules for autonomous systems shipped to production or deployed in real-world operations.

  • Strong programming skills in C++ (preferred) or Python, and experience with Linux-based operating systems.

  • Demonstrated ability to take ambiguous technical problems and drive them to well-architected solutions independently.

  • Excellent communication skills, proactiveness, and a strong sense of ownership.

We Prefer:

  • MS or Ph.D. in Computer Science, Robotics, or a related field.

  • Mastery of Modern C++ (14 and beyond) and safety-critical coding practices (e.g., MISRA, ISO 26262).

  • 5+ years of industry experience in planning for robotic ground vehicles.

  • In-depth understanding of DDS frameworks like ROS/ROS2 or other networking middleware.

  • Experience in startup environments, demonstrating adaptability to rapidly changing priorities.

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