Fleet Response Engineer

Rhoda AI•Mountain View, CA

20h

About The Position

At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality.

Requirements

Strong systematic debugging of complex systems — the ability to reason from symptoms to root cause and reverse-engineer unexpected behavior.
Comfortable in Linux and the command line, and reading logs, telemetry, and system data.
Coding proficiency in Python and/or C/C++ (Bash a plus).
Clear written and verbal communication, and calm judgment under pressure.
Willingness to take part in an on-call rotation, including some nights and weekends as the fleet grows.

Nice To Haves

3+ years working with robotic, autonomous, automotive, aerospace, or industrial-automation systems in an engineering, reliability, or support capacity.
Familiarity with ROS/ROS2 and robot subsystems (sensors, actuators, perception, networking).
Prior on-call, site-reliability, or release-engineering experience.
Experience building tools that help others debug, and a track record of solving unusual bugs.
Comfort with hardware and hardware–software interfaces; willingness to travel occasionally to deployment sites.

Responsibilities

Triage and incident response: Monitor incoming faults, alarms, and alerts from robots deployed at customer sites and in internal testing; triage and prioritize by severity and operational impact.
Act as the first engineering responder and point of contact for real-time escalations from field technicians and operations.
Debug complex issues across subsystems through log analysis, telemetry review, and reproduction testing.
Drive incidents to fast resolution or mitigation to restore operation and maximize fleet uptime.
Escalate to and coordinate with domain engineering teams (AI, robot software, cloud, hardware) to drive resolution.
Own the on-call rotation and paging, and keep the escalation process clear and current.
Communicate status to operations, engineering, and customer-facing teams throughout an incident.
Own each incident through to confirmed recovery and a clean handoff.
Perform root-cause analysis — identify contributing factors, themes, and corrective actions — and track follow-ups to closure.
Document investigations and fixes in a shared knowledge base and troubleshooting guide so future issues resolve faster.
Feed field insights back to engineering to improve product reliability and issue detection.
Track reliability trends and flag recurring or systemic failures.
Build (or spec, with the software team) the monitoring, alerting, and diagnostic tooling that catches issues fleet-wide.
Establish diagnostic procedures that let technicians and operators self-serve common issues.
Continuously reduce manual, repetitive response work through automation.