Senior/Staff Behavior Planning Engineer

Gatik AI • Mountain View, CA

3d • $180,000 - $260,000 • Onsite

About The Position

We’re seeking Senior or Staff Engineers to help build the core behavior planning system for autonomous vehicles, enabling safe and intelligent decision-making. The role involves designing behavior tree architectures, developing robust C++ infrastructure, collaborating across autonomy teams, evaluating planner performance, and providing technical leadership within the team.
This role is onsite 5 days a week at our Mountain View, CA office!

Requirements

• Ph.D. with 3+ years or Master’s with 5+ years of industry experience in robotics, autonomous systems, or behavior planning.
• Proven experience in behavior planning, including use of behavior trees, finite state machines, or rule-based planners in autonomous driving or robotics applications.
• Strong proficiency in C++ with a deep understanding of performance, memory management, and software architecture in production systems.
• Solid understanding of motion planning and prediction interfaces, with experience building real-time, safety-critical systems.
• Strong debugging, system thinking, and collaborative communication skills.

Nice To Haves

• Knowledge of diffusion models and/or Vision-Language-Action (VLA) models is a strong plus.

Responsibilities

• Design, implement, and maintain the core behavior planning system for autonomous vehicles, enabling intelligent, interpretable, and safe decision-making in complex real-world scenarios.
• Develop and extend behavior tree architectures for hierarchical decision logic, including support for mission planning, tactical maneuvers, and contingency handling.
• Collaborate closely with the motion planning, prediction, and control teams to ensure seamless transitions from high-level decisions to executable trajectories.
• Build and optimize C++-based software infrastructure for behavior planning, including tools for simulation, debugging, visualization, and closed-loop testing.
• Evaluate planner performance in diverse real-world and simulated environments; identify failure modes and develop strategies to improve robustness and generalization.
• Participate in design reviews and system integration across the full autonomy stack.
• Provide technical leadership, mentorship, and architectural guidance for junior team members.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree