Robotics Test & Debug Engineer

Tutor Intelligence•Watertown, MA

1d•$120,000 - $200,000•Onsite

About The Position

Tutor is hiring its first quality and reliability engineer to build the quality and reliability function for production. The role owns determining whether robots are ready to ship and investigating what fails and why, with authority to hold robots that do not meet quality requirements. The position reports to the Head of Manufacturing and is onsite in Watertown, Massachusetts, with up to 25% travel to customer sites and suppliers. The initial priority is returned-material containment, Material Review Board (MRB) work, failure analysis, and supplier RMAs. The engineer will then establish incoming and finished-robot quality gates, build and operate a FRACAS using AI tools such as Claude on top of manufacturing execution system (MES) data, field tickets, and robot telemetry, and provide teams with regular data-based quality and reliability reporting. The role involves investigating robot arms, control boxes, PCBAs, drives, power systems, sensors, and harnesses, directing technicians during teardowns and bench tests, and verifying corrective actions. Production Engineering builds tests identified as needed; this engineer defines requirements and verifies the tests catch failures. Success in the first 90 days means returned parts have owners, statuses, and root-cause paths; weekly MRB is data-driven; supplier RMAs have failure-analysis results and supplier responses; and teams are using a live failure dashboard. Within a year, field escapes should trend toward zero, repeat failures should be measurably reduced, incoming and shipping gates should be defined and largely automated, and leadership should be able to get quality answers from the data.

Requirements

Personally driven production or field failures on electromechanical hardware to a verified root cause and corrective action.
At least 4 years of experience in quality, reliability, test, or hardware engineering.
Bachelor's degree in Electrical, Mechanical, Computer Engineering, or a related field.
Experience working directly with suppliers on RMAs and corrective actions.
Experience building tools with AI, such as scripts, dashboards, or automated checks, that other people used; candidates should be prepared to discuss an example.
Python or SQL skills to analyze failure data and develop clear conclusions.
Able to travel up to 25%.

Nice To Haves

Robotics, industrial automation, or hardware startup experience.
Hands-on electrical debugging of motor drives, power, and communication faults.
Failure analysis experience with robot arms, servo motors, or gearboxes.
Reliability engineering experience with life testing, HALT/HASS, Weibull analysis, and MTBF analysis.
Experience with MES and serial-number traceability systems.
ASQ CQE or CRE certification.

Responsibilities

Contain failures by quarantining suspect stock and identifying potentially affected robots in the factory and field.
Run the weekly Material Review Board, including dispositions, root-cause-analysis owners, and corrective actions through closure.
Own failure analysis for returned parts and field failures, including robot arms, control boxes, PCBAs, drives, power systems, sensors, and harnesses.
Direct technicians during teardowns and bench tests, determine root causes, and verify that fixes work.
Build and operate a FRACAS using AI tools and data from the MES, field tickets, and robot telemetry.
Track failures by component, supplier, and serial number, including repeat failures and escapes.
Set reliability targets such as MTBF and failure rate for critical subsystems and track factory and fleet performance.
Provide Engineering, Manufacturing, Deployment, and Customer Success with regular data-based quality reporting and feed findings into design reviews.
Serve as the technical point of contact for supplier RMAs; provide failure data and analysis, seek supplier root causes, issue SCARs, and pursue corrective actions, credits, and replacements.
Set pass/fail criteria for incoming parts and finished robots and make ship-or-hold decisions.
Define needed tests when failures reveal gaps, then verify tests built by Production Engineering catch the failures.
Qualify new parts, refurbished parts, and supplier changes before they reach the production line.
Build AI-powered scripts, dashboards, or automated checks used by other people.
Travel to customer sites and suppliers as needed, up to 25%.