Skip to content

Engineering Manager - Behavior

Leads engineering team building scalable behavior systems for autonomous vehicles across cars, trucks, mining, construction, and offroad. Owns strategy, architecture, and delivery of safety-critical algorithms; requires 5+ years in robotics/autonomy and team management experience.

About the job

Responsibilities

  • Drive the overall strategy, technical roadmap, and architecture for behavior planning dedicated to L2 and L4 autonomous vehicles for cars, trucks, mining & construction, and offroad.
  • Guide the design and implementation of robust, safety-critical algorithms for various driving domains, including urban streets, highways, dirt roads, and diverse environmental conditions.
  • Grow and manage a team of world class engineers in the field of behavior systems.
  • Evolve the architecture to achieve the final goal of an L4 end-to-end stack.
  • Work cross functionally with other teams, including Perception, Research, Simulation, and Vehicle Operations, to ensure the robust and efficient integration of the behavior software stack.

Requirements

  • 5+ years of experience in robotics or autonomous systems, with a focus on behavior systems.
  • Experience in two or more of the following: behavior planning, decision making under uncertainty, path planning, motion planning, probabilistic reasoning, prediction, machine learning, trajectory generation, mapless driving, end-to-end autonomy stack.
  • Demonstrated ability to architect large-scale, production software for real-world robotic or automotive systems.
  • Proven leadership experience managing engineering teams, setting goals, and overseeing technical projects.
  • Strong communication and problem-solving skills.

Nice to Haves

  • Direct experience working in end-to-end autonomy.
  • Hands-on experience building ML-driven and rule-based behavior planning (and their interplay), intent detection, or risk assessment modules.
  • Demonstrated success in applying machine learning and AI processes to complex decision-making frameworks for autonomous vehicles.

Compensation

Base salary range: $204,000 - $343,000 USD annually, plus equity and benefits.

Skills

Behavior Planning, Motion Planning, Path Planning, Machine Learning, Autonomous Systems, Probabilistic Reasoning, Prediction, Trajectory Generation, End-To-End Autonomy, Robotics

Genius AI

Genius AI

New York, NY
Engineering Manager, Platform
$200k+/yrHybrid5+ YOEEngineering Management

Leads a platform engineering team responsible for shared systems, identity, permissions, session management, and messaging infrastructure. The manager owns delivery and architecture, develops engineers, embeds AI into development workflows, and partners closely with Product and Design.

Datadog

Datadog

New York, NY

Manager I, Engineering - Cloud FinOps
$200k+/yrHybrid5+ YOEEngineering Management

Engineering manager leading a data platform team that allocates cloud costs to products and customers. The role requires experience with reproducible batch pipelines, versioned financial metrics, cross-functional delivery, and cloud cost, billing, revenue, or financial data systems.

Stellar Cyber

Stellar Cyber

United States

Integration Software Engineering Manager
$200k+/yrRemote5+ YOEEngineering Management

Leads a hands-on team building and maintaining third-party security and enterprise integrations. The manager coaches engineers, guides technical decisions and delivery, and contributes to backend systems, APIs, and production troubleshooting.

Commure

Commure

Mountain View, CA
Engineering Manager, AI Integrations
$200k+/yrHybrid5+ YOEEngineering Management

Leads the engineering team building an AI-powered referral coordination product integrating document processing, voice automation, and EHR systems. The role combines people management, hands-on technical leadership, scalable architecture, customer collaboration, and healthcare interoperability expertise.

Chime

Chime

New York, NY
Engineering Manager, AI & App Experience
$199k+/yrOn-site5+ YOEEngineering Management

Leads and develops a 4–5 person engineering squad while continuing to write production code and owning delivery, architecture, and operational health. The role focuses on safely shipping LLM-powered financial experiences and requires people-management experience, AI-native development fluency, and hands-on software engineering skills.