Principal Engineer, Autonomy
AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers operate. Backed by top-tier venture capital, we serve some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.
About the role
We are hiring a Principal Engineer for Autonomy, the senior-most individual contributor in our autonomy organization. Reporting directly to the VP of Engineering, you will have deep technical ownership of one or more of Perception, Prediction, and Planning, influencing the entire autonomy stack.
Responsibilities
Own the design and evolution of the perception stack — detection, classification, tracking, and multi-modal sensor fusion across available modalities.
Drive perception robustness across real-world operating conditions and set the direction for deep learning applications.
Own the prediction stack and design models for intent inference, behavior forecasting, and handling occlusions and edge cases.
Set the direction for prediction integration with perception and planning.
Own the planning and decision-making stack, from structured driving behaviors to domain-specific maneuvers for autonomous GSE operations.
Set the direction for learned components in the planner.
Set technical direction at interfaces between your primary areas and the rest of the stack.
Partner with other senior engineers to ensure the system remains coherent end-to-end.
Own the functional and software architecture of the autonomy stack and collaborate with neighboring teams for implementation.
Requirements
15+ years of hands-on experience building production autonomy systems, with strong technical depth across multiple modules (localization, perception, prediction, planning, controls).
Demonstrated track record of shipping autonomy components in production on real vehicles at non-trivial scale.
Prior experience as the most senior individual contributor in an autonomy organization, setting direction, mentoring staff/senior engineers, and partnering with engineering leadership.
Deepest technical depth in perception, prediction, or planning (ideally more than one of the three).
Strong software engineering fundamentals in C++ and Python.
Experience with modern deep learning for autonomy, including practical realities of model training, evaluation, deployment, and lifecycle management.
Experience working in or with ROS / ROS 2 and distributed-systems realities of on-vehicle compute.
A bias for execution. Ship, close out problems, convert ambiguity into a plan, and turn plans into running code on a vehicle.
Preferred
Experience with safety-critical or functional-safety-relevant systems (ISO 26262, ISO 13849, SOTIF, or aerospace equivalents).
Experience operating in an Operational Design Domain involving heavy human interaction, mixed traffic, or unstructured environments.
Familiarity with simulation-driven verification and using simulation in a CI/CD pipeline for autonomy.
Benefits
The role offers a defined path to scale, a real commercial deployment, and a concrete path to removing the safety driver and scaling the fleet. Your work has a destination.
Pay
$300K - $350K