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Posted 14 days ago

Senior Software Engineer, Behavior Planning

@ AeroVect

Toronto, ON · Vancouver, BC

$160k–$200k/yrRemoteFull-time3+ years experience
Apply now
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Overview

AeroVect is hiring a Senior Software Engineer to design and build behavior planning systems for autonomous vehicles operating in airside ground-handling environments. The role owns key modules of the decision-making layer, spanning multi-agent interaction, rule-based and learned planning, and edge-case handling.

Pay:

$160,000–$200,000 a year

Responsibilities:

  • Develop behavior planning algorithms for autonomous vehicles
  • Design and maintain C++ and Python planning code
  • Test in simulation and real-world scenarios
  • Analyze performance and implement enhancements
  • Document code, algorithms and system designs

Requirements summary:

  • Master's degree in Computer Science, Robotics or related field
  • Minimum 3 years of industry experience in autonomous driving or robotics
  • Proficient in modern C++ and object-oriented programming
  • Knowledge of state machines and behavior trees
  • Familiarity with A*, RRT or optimization-based planning

Tools & skills

Source and dates

Employer career site / ATS feed · ashby

Employer posting date
2026-10-23
First seen by our source
2026-10-23
Source record updated
2026-10-23

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Job details

SenioritySenior
DepartmentSoftware development
Experience3+ years
Hours per week40 (estimated)
Work settingOffice, Client sites
PositionMostly sitting
Physical demandsphysical low · computer high
EducationMaster’s degree (required)
Fields of studyComputer Science, Robotics

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.

FieldValue
IndustryAirlines and Aviation
Company size51-200 employees
HeadquartersSouth San Francisco, California
Organization typePrivately Held
Year founded2020
SpecialtiesAviationAutonomous DrivingAerospaceTransportationLogisticsAirport AutomationPhysical AIand Artificial Intelligence
Open jobs on Jobsy15
LinkedInView page
Job description

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

In this role, you'll own the design and implementation of key modules in the behavior planner — the decision-making layer that determines what the vehicle should do in complex, dynamic airside scenarios. You'll work at the intersection of mission-level goals and motion-level execution, tackling problems in multi-agent interaction modeling, rule-based and learned decision-making, and robust handling of edge cases unique to airport ground operations.

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

  • 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

You Have

  • Proficient in modern C++ (11/14/17) and object-oriented programming

  • Skilled in Python for rapid prototyping and testing

  • Strong in debugging, profiling, and optimizing code

  • 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

We Prefer

  • Knowledge of state machines, behavior trees, and decision-making under uncertainty

  • Expertise in path planning algorithms such as A*, D*, and Rapidly-exploring Random Trees (RRT)

  • Knowledge of machine learning techniques, especially in the context of behavior prediction and planning

  • Experience with ROS / ROS2

  • Implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environment

  • Ensuring that behavior planning algorithms can execute with minimal latency for real-time navigation

  • Proficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertainty

  • Master’s degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plus

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