Product Quality Engineer
Quick Summary
Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team,
- Lead the internal APQP process, focusing on design maturity milestones and ensuring the transition from prototype to production (SOP).
- Work with Hardware Engineering on the Design PPAP deliverables, including Standards, Requirements, Changes, Design Documentation, DFMEAs. Identifying special characteristics (SCs/CCs), ensuring design risks are identified and managed.
- Partner with Hardware and Software Engineering to develop specialized End-of-Line (EOL) testers and calibration fixtures that validates the product design, supporting production assembly verification.
- Own the RCCA (Root Cause Corrective Action) process for system-level and field-reported failures, using 8D methodology to solve complex issues that span hardware, software, and environmental factors.
- Support Reliability Engineering DV (Design Verification) and PV (Process Verification) test plans, ensuring the fully assembled robot can withstand automotive-grade environmental challenges over its intended service life.
- Lead technical quality interactions with OEM partners, ensuring our hardware/software integration meets their vehicle-level quality standards and rigorous safety gates.
- Manage vehicle integration with OEM partners, overseeing vehicle integration quality from implementation through Start of Production (SOP) and production support.
- Analyze Field Quality data to identify hardware issues and problems, informing opportunities for engineering improvements.
- Collaborate with Service and Operations teams to develop service procedures, field service bulletins, and repair procedures.
- Support Service and Operations teams with fleet reworks, rollouts, and recalls.
- Support internal R&D and early maturity builds by acting as the technical product quality lead on the floor, resolving assembly discrepancies and managing non-conforming material (MRB).
- Be QMS responsible for managing and improving Waabi’s quality management system.
Requirements
~2 min read- Bachelors of Science in Mechanical Engineering, Electrical Engineering, or a related technical field.
- Expertise in APQP & PPAP Frameworks: Deep understanding of how to apply automotive quality standards to a fast-moving tech environment.
- Problem-Solving Mastery: Expert in 8D, 5-Why, and Fishbone analysis, with a focus on system-level interactions (e.g., how field-driven vibration affects an optical sensor's calibration).
- Experience with PLM & Version Control: Skilled in managing complex Bills of Materials (BOMs) and ensuring software/firmware versions are tracked alongside hardware revisions.
- Proficient with Solidworks & Technical Drawings: Ability to review complex assemblies, perform tolerance stack-up analysis, and interpret GD&T.
- Experience with various manufacturing processes (e.g. printed circuit board, PCBA, wire harness, sheet metal, injection molding, stamping, die casting, and CNC machining).
- Experience with Finite Element Analysis (FEA) to evaluate designs and identify design challenges or issues that may be mitigated to improve manufacturability and product quality.
- Reliability & Analytics: Experience analyzing and using data to predict product life and drive improvements.
- Experience with automotive standards (e.g. ISO 9001, IATF 16949 or ISO 26262).
- Travel Expectations: Approximately 25% travel required. This is objective-based and fluctuates according to program milestones and product quality needs.
Requirements
~1 min read- Automotive, Aerospace, Autonomous Vehicle (AV) or EV industry experience is highly preferred.
- IPC/WHMA-A-620 and IPC-A-610 knowledge for acceptance of wire harness assemblies and electronic assemblies.
- Certified Quality Engineer (CQE) or Six Sigma Black Belt.
Listing Details
- Posted
- April 1, 2026
- First seen
- April 2, 2026
- Last seen
- April 26, 2026
Posting Health
- Days active
- 23
- Repost count
- 0
- Trust Level
- 31%
- Scored at
- April 26, 2026
Signal breakdown

Waabi is an AI company developing generative AI-powered autonomous driving technology for long-haul trucking, aiming for commercial deployment in 2025.
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