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.