Head of QA

• Build and lead Amazon RIVR’s end-to-end QA organization across the full System, Autonomy, Hardware, and Operations from "A to Z". • Define and implement a scalable quality strategy for robotics fleets inspired by autonomous vehicles and robotics best practices. • Establish a unified validation workflow to break down silos and transition from engineer-led testing to a centralized, automated pipeline. • Partner closely with Software and Hardware Engineering to embed quality early in the development lifecycle, acting as a technical partner rather than a corporate gatekeeper. • Architect and scale a Hardware-in-the-Loop (HiL) farm to automate the testing of complex mechatronic variables. • Develop automated testing frameworks across Software-in-the-Loop (SiL), Hardware-in-the-Loop (HiL), and real-world testing. • Take ownership of safety governance and establish high-velocity pipelines (e.g., 14-day fixes) for critical field safety reports. • Define quality KPIs, release criteria, and reliability targets at robot and fleet scale. • Oversee field quality, maintenance feedback loops, and operational performance monitoring. • Drive root-cause analysis and continuous improvement across hardware and software failures. • Scale QA infrastructure, tooling, and team processes to support the target of manufacturing up to two million robots.
• Pioneer Leadership experience: 10+ years leading QA or Validation teams with a proven track record of building departments in high-growth environments. • Proven experience leading QA or Validation teams in robotics, autonomous vehicles, automotive, or other safety-critical systems. • Track record of building scalable quality processes for both hardware and software products. • Deep understanding of validation methodologies across SiL, HiL, and real-world testing. • Strong mechatronic and systems engineering mindset with the ability to bridge Hardware, Firmware, and AI/ML Autonomy. • Hands-on mastery of automation frameworks, test infrastructure (e.g., dSPACE), and regression pipelines. • Ability to work cross-functionally with Software, Hardware, and Product teams in fast iteration cycles. • Experience with safety, compliance (e.g., UL2, ISO 26262), and field reliability feedback loops. • Comfortable operating in high-growth startup environments with evolving processes and products
• Experience in autonomous driving, mobile robotics, or last-mile delivery robots. • Advanced degree (MSc/PhD) from top-tier engineering institutions. • Experience validating AI/ML or Vision-Language-Action (VLA) autonomy systems. • Background in simulation environments and large-scale scenario testing. • Experience scaling QA organizations from R&D prototypes to high-volume mass deployment. • Knowledge of regulatory certification processes for robots operating in public spaces. • Familiarity with MLOps pipelines and continuous integration for robotics.