This posting is no longer listed by Rhoda Ai.
hirly last saw it live on 1 September 2026. Similar roles are on the live board.
Rhoda Ai
Fleet Response Engineer
Mountain View
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hirly's read of this role
- Seniority
- Mid level
- Work mode
- On-site / unstated
- First seen by hirly
- 1 Sept 2026
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the posting
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.
The Role
You'll be the first engineer in the loop when something goes wrong on a deployed robot. When the field or operations team hits an issue they can't resolve, they come to you. You'll triage incoming faults and alerts, debug across the full stack: hardware, embedded, software, sensors, networking, to find the fastest safe path back to operation, and pull in the right domain experts when an issue runs deep. You'll own incidents from first alert through recovery and root cause, and turn what you learn into better monitoring, better runbooks, and a more reliable fleet.
What You'll Do
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
Escalation and coordination
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
Root cause and reliability
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
Tooling and prevention
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
Required Qualifications
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
Preferred Qualifications
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
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