Director of Behaviors and Planning

Overland AI•Seattle, WA

1d•$200,000 - $300,000•Onsite

About The Position

Overland AI builds autonomous ground vehicles for defense and national security missions. Our Behaviors & Planning team owns the final layer of single-vehicle autonomy: using terrain understanding to generated planned paths and execute behaviors. This is the core autonomy loop that makes our vehicles move safely and reliably across operational domains ranging from secondary roads to complex off-road terrain. We are looking for a Director to lead this team. You will manage 7-10 engineers working across motion planning, on-vehicle behaviors, geospatial planning, and offline verification. You will set technical direction for how our vehicles navigate the world autonomously, partner closely with our ML & Perception team to drive tighter integration between learned terrain models and classical planning, and own the verification systems that prove our autonomy works before it reaches the field. This is a hands-on leadership role. You will shape the technical roadmap, make architecture decisions, mentor engineers, and represent your team's capabilities and needs across the organization. The work matters: soldiers depend on our vehicles to operate reliably in contested, communication-degraded, and GPS-denied environments.

Requirements

PhD in robotics, computer science, controls, or a closely related field, with a research focus in motion planning, autonomous navigation, or robot decision-making
5+ years of professional experience beyond the PhD, shipping autonomy software in industry
2+ years leading an engineering team, including setting technical direction, managing individual contributors, and delivering complex systems on a timeline
Deep technical expertise in at least two of: sampling-based or optimization-based motion planning (e.g., MPPI, RRT, trajectory optimization), costmap-based navigation, behavior architecture and state machines, vehicle control systems, or simulation/verification frameworks
Experience shipping autonomy to hardware -- you have put your planning and behaviors stack on a real robot and seen it operate in unstructured environments, not just in simulation
Strong partnership instincts -- you know how to work effectively across team boundaries, particularly at the perception-planning interface where two teams must co-own system performance
Clear communication -- you can explain complex technical tradeoffs to engineers, executives, and customers. You write well and think clearly under pressure
Comfort with ambiguity and operational tempo -- defense programs move fast, requirements shift, and field events don't wait. You thrive in this environment
Must be a U.S. Person, as defined under ITAR, and eligible to obtain and maintain a U.S. security clearance. Active Secret clearance is preferred but not required at the time of hire.

Nice To Haves

Experience with off-road or unstructured terrain navigation (not just highway/urban AV)
Familiarity with ROS2 or similar robotics middleware
Background in machine learning for planning or perception-planning integration (learned cost functions, end-to-end planning, foundation models for robotics)
Experience with geospatial planning, satellite imagery-based route planning, or GIS data for autonomy
Prior work in defense, government contracting, or DoD customer engagement
Experience building simulation and log-replay verification systems for autonomous vehicles

Responsibilities

Lead, manage, mentor, and grow a team of 7-10 engineers spanning planning, behaviors, and verification.
Run sprint planning and set technical priorities.
Build a team culture that values engineering rigor and field-validated results.
Drive the technical direction for single-vehicle autonomous movement: local and mid-range planning (MPPI, costmap-based approaches), global/geospatial planning, behavior management (teleop, autonomous modes, trail-keeping, convoy following), and task interfaces.
Ensure the system is safe, performant, and reliable across our full operational design domain.
Co-own the contract between the Behaviors & Planning team and the ML & Perception team, driving tighter integration as we move toward end-to-end learned planning approaches.
Own offline verification of autonomy requirements through simulation, log playback, and automated regression testing.
Invest in tooling and infrastructure that lets your team catch regressions before they reach vehicles.
Explore and integrate emerging capabilities such as VLM-based reasoning for behavioral guardrails, scene understanding, and contextual decision-making.
Support field deployments and customer demonstrations.
Understand soldier workflows and operational needs firsthand.
Translate field observations into engineering priorities.