Posted 3 months ago
Principal Engineer, Autonomy
@ AeroVect
Toronto, Ontario
Overview
AeroVect is hiring a Principal Engineer for Autonomy, the senior-most individual contributor in its autonomy organization, reporting to the VP of Engineering. The role owns deep technical design across Perception, Prediction and Planning for autonomous ground support equipment at airports, with cross-stack influence and no direct reports. Full-time, with a requirement of 15+ years building production autonomy systems.
Responsibilities:
- Own design of perception, prediction or planning stack
- Set technical direction across autonomy architecture
- Partner with senior engineers on end-to-end system coherence
- Guide learned components in planning and perception
- Drive autonomy architecture implementation with neighboring teams
Requirements summary:
- 15+ years building production autonomy systems
- Track record shipping autonomy on real vehicles
- Deep technical depth in perception, prediction or planning
- Strong C++ and Python engineering fundamentals
- Experience with ROS / ROS 2 and on-vehicle compute
- Prior experience as most senior IC in autonomy
Tools & skills
Source and dates
Employer career site / ATS feed · ashby
- Employer posting date
- 2026-07-27
- First seen by our source
- 2026-10-08
- Source record updated
- 2026-10-09
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Experience | 15+ years |
| Hours per week | 40 (estimated) |
| Work setting | Office, Client sites |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
AeroVect
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
The Airport Automation Company
Full company description
AI-powered airport logistics automation solutions, trusted by the world's largest airlines and airports.
- LinkedIn followers
- 5,376
- People associated on LinkedIn
- 63
- Reported office locations
- 233 E Harris Ave, South San Francisco, California 94080, US
- Toronto, Ontario, CA
- Atlanta, Georgia 30308, US
- Frankfurt, DE
- New York, 10007, US
- Business categories
- Air Transportation
- Robotics
- Software
- Logistics
- Transportation
- Artificial Intelligence (AI)
- Aerospace
- Autonomous Vehicles
- Manufacturing
- Other recorded names
- AeroVect
- Specialties
- Aviation
- Autonomous Driving
- Aerospace
- Transportation
- Logistics
- Airport Automation
- Physical AI
- and Artificial Intelligence
- Profile identifies a recruitment agency
- No
- Reported total investment
- 27,000,000
Currency and observation date were not supplied; this is not a current valuation or a funding round.
AI-powered airport logistics automation solutions, trusted by the world's largest airlines and airports.
| Field | Value |
|---|---|
| Industry | Airlines and Aviation |
| Company size | 51-200 employees |
| Headquarters | South San Francisco, California |
| Organization type | Privately Held |
| Year founded | 2020 |
| Specialties | AviationAutonomous DrivingAerospaceTransportationLogisticsAirport AutomationPhysical AIand Artificial Intelligence |
| Open jobs on Jobsy | 15 |
| View page |
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.
We are hiring a Principal Engineer for Autonomy — the senior-most individual contributor in our autonomy organization. You will have the deepest hands-on technical ownership of one or more of Perception, Prediction, and Planning, with cross-stack influence across the rest of the autonomy stack. You will report directly to the VP of Engineering, with no direct reports of your own, but with the expectation that you set technical direction the rest of the autonomy team follows.
We are looking for someone who is excellent both at the systems level and at execution — a senior IC with the technical depth to anchor the hardest decisions in autonomy and the bias for shipping to convert those decisions into running code on a vehicle.
You Will
You are the senior-most IC in autonomy, with the deepest technical ownership of either Perception, Prediction, or Planning (or any combination thereof) and influence across the rest of the stack.
Perception. Own the design and evolution of the perception stack — detection, classification, tracking, and multi-modal sensor fusion across the available modalities. Drive perception robustness across the long tail of real-world operating conditions, and set the direction for where and how deep learning is best applied across the perception pipeline.
Prediction. Own the prediction stack and the design of models for intent inference, behavior forecasting, and handling occlusions and edge cases. Set the direction for how prediction integrates with perception upstream and planning downstream.
Planning. Own the design of the planning and decision-making stack, from structured driving behaviors to the domain-specific maneuvers required for autonomous GSE operations. Set the direction for where learned components earn their place in the planner.
Cross-stack influence. Set the technical direction at the interfaces between your primary areas and the rest of the stack, and partner with the other senior engineers in autonomy to keep the system coherent end-to-end.
Autonomy architecture. Own the functional and SW architecture of the autonomy stack, and partner with neighboring teams towards its implementation.
You Have
15+ years of hands-on experience building production autonomy systems, with strong technical depth across multiple modules (localization, perception, prediction, planning, controls). You think at the level of the autonomy system, not a single module.
Demonstrated track record of shipping autonomy components that have run in production on real vehicles at non-trivial scale — not just research prototypes or simulation results.
Prior experience as the most senior individual contributor in an autonomy organization — setting direction, mentoring staff/senior engineers, and partnering with engineering leadership without managing a team yourself.
Deepest technical depth in perception, prediction, or planning (ideally more than one of the three).
Strong software engineering fundamentals in C++ and Python. You write or review code that other senior engineers want to extend and trust in a safety-relevant system.
Fluency with modern deep learning for autonomy, including the practical realities of training, evaluation, deployment, and lifecycle management of models that have to work in the real world.
Experience working in or with ROS / ROS 2 and the distributed-systems realities of on-vehicle compute (real-time constraints, IPC, fault containment).
A bias for execution. You ship. You close out problems. You convert ambiguity into a plan and the plan into running code on a vehicle.
We Prefer
Experience with safety-critical or functional-safety-relevant systems (ISO 26262, ISO 13849, SOTIF, or aerospace equivalents).
Experience operating in an Operational Design Domain that involves heavy interaction with humans, mixed traffic, or unstructured environments.
Familiarity with simulation-driven verification and the use of simulation as part of a CI/CD pipeline for autonomy.
Why this role at AeroVect?
A real ODD with real constraints. Airports are one of the few environments where commercial autonomy is genuinely viable today and where the path to removing the safety driver is concrete rather than speculative.
Scope. This is the senior autonomy IC role at AeroVect. You are the senior-most technical voice across Perception, Prediction, and Planning, with cross-stack influence across the rest of the autonomy stack.
A defined path to scale, not a science project. A real commercial deployment with a concrete path to removing the safety driver and scaling the fleet. Your work has a destination.
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