Job Overview
Location
South San Francisco - Hybrid
Job Type
Full-time
Category
Software Engineering
Date Posted
June 4, 2026
Full Job Description
đź“‹ Description
- • Lead the end-to-end development and execution of AeroVect’s autonomy stack, encompassing Perception, Prediction, Planning, Controls, and Localization modules.
- • Own the multi-year technical roadmap for autonomy, defining architectural direction across modular and end-to-end approaches to meet commercial deployment goals.
- • Manage a team of 15+ engineers across all autonomy disciplines, including hiring, leveling, and growing senior and staff-level individual contributors.
- • Establish and run the operating cadence of the autonomy organization, including planning, prioritization, technical reviews, and performance management.
- • Serve as the primary autonomy interface to Systems, Safety, Platform, Hardware, Simulation, and Product teams, owning cross-functional trade-offs and integration points.
- • Remain deeply technical: actively participate in design reviews, challenge technical decisions with substance, and debug complex system-level problems alongside engineers.
- • Deliver production-grade autonomy components that operate on real vehicles at non-trivial scale, with proven results beyond simulation or research prototypes.
- • Ensure autonomy systems are built with real-world operational constraints in mind, including real-time performance, fault containment, and IPC in on-vehicle compute environments.
- • Apply modern deep learning practices to autonomy, including model training, evaluation, deployment, and lifecycle management for systems that must function reliably in dynamic environments.
- • Work with ROS / ROS 2 and distributed systems architectures under strict real-time and safety-critical constraints.
- • Drive execution with a bias for shipping: convert ambiguity into actionable plans and deliver running code on physical vehicles.
- • Maintain direct accountability for the technical and organizational success of the autonomy organization, reporting directly to the VP of Engineering.
- • Operate within an Operational Design Domain (ODD) involving heavy human interaction, mixed traffic, and unstructured environments — specifically airport ground handling operations.
- • Leverage simulation-driven verification and integrate simulation into CI/CD pipelines for autonomy validation and testing.
- • Ensure autonomy systems align with safety-critical standards, including ISO 26262, ISO 13849, SOTIF, or aerospace-equivalent frameworks.
- • Build and scale an autonomy organization with a clear path to removing safety drivers and deploying fleets commercially at scale.
🎯 Requirements
- • 15+ years of hands-on experience building production autonomy systems across multiple modules (localization, perception, prediction, planning, controls)
- • Demonstrated track record of shipping autonomy components in production on real vehicles at non-trivial scale
- • Direct management experience of an autonomy or robotics team of 15+ engineers, including senior and staff-level ICs
- • Fluency with modern deep learning for autonomy, including training, evaluation, deployment, and lifecycle management of real-world models
- • Experience working with ROS / ROS 2 and distributed-systems realities of on-vehicle compute (real-time constraints, IPC, fault containment)
- • Demonstrated end-to-end ownership of an autonomy stack
🏖️ Benefits
- • Lead the senior autonomy leadership role at a Series A company backed by top-tier venture capital in aviation and autonomous driving
- • Work on a real, viable Operational Design Domain (airports) with a concrete path to removing safety drivers and scaling fleets
- • Own the entire autonomy stack and team with clear scope and commercial deployment goals
- • Join a company with established customers including some of the world’s largest airlines and ground handling providers
Skills & Technologies
Python
REST
Hybrid
About AeroVect Inc.
AeroVect Inc. builds autonomous ground vehicles and management software for airport cargo and baggage handling. Its electric tractors and tow-tugs automate loading, unloading, and transport of luggage and freight on tarmacs and in terminals, integrating with existing baggage systems and aircraft operations. The company combines AI perception, path planning, and fleet orchestration to reduce delays, labor costs, and emissions while improving ramp safety and throughput for airlines and ground-handling partners.
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