Mgr, Quality/Training Strategy, GO-AI Operations Integration

Location: Bangalore; Hyderabad, India

Description
The Manager, Quality & Training Strategy owns how GO-AI defines, measures, and improves the quality of annotations delivered to Amazon Robotics and Worldwide Operations science teams. You will own the quality model for an AI and ML annotation workforce: how accuracy is measured, how measurement scales across use cases and demand, and how quality standards reflect the customer's perception of the output they receive. You operate as the independent measurement function for the annotation business, providing defect insights to Operations while representing the customer's view of quality.
As GO-AI evolves, this role ensures that quality measurement keeps pace with how annotations are consumed by data scientists inside an ML product development lifecycle, and increasingly alongside model-generated output. You lead a team of program managers and quality managers across India and Costa Rica, and you apply an up-to-date understanding of AI capabilities to identify and drive use cases that improve operational metrics.
Key job responsibilities

• Own the GO-AI quality model. Define how annotation accuracy is measured for each use case so that published metrics reflect the customer's perceived quality of the output.
• Own quality KPI definition and governance across 70+ use cases, including target baselining, process capability assessment, and the standards applied to new and ramping workforces.
• Define the quality measurement strategy, including how coverage and depth of measurement scale with demand, risk, and cost of quality.
• Lead deep dives on any degradation of customer-consumed quality metrics, drive to root cause through standardized mechanisms, and publish findings and corrective actions to senior leadership through weekly and monthly business reviews.
• Operate as the independent measurement function for the annotation business. Partner with Customer Tech Programs on customer quality and speed expectations, and with Operations business unit leaders on defect insights and remediation.
• Translate ML customer needs into quality standards. Understand how annotations feed model training and evaluation so that quality definitions match how data scientists consume the output.
• Maintain a current understanding of AI capabilities and how they function. Identify and drive use cases where AI tooling improves quality, speed, and experience.
• Lead and develop a geographically distributed team of 6 to 8 program managers and quality managers across India and Costa Rica. Own hiring, onboarding, performance management, career growth, and team structure.

About the team
GO-AI is a technology enablement organization that accelerates the development and enhances the performance of AI-based robotic and automation solutions for Amazon Robotics (AR) and key Worldwide Operations programs. We combine human expertise with machine learning to produce high-quality training data, validate model outputs, and continuously improve AI system performance across many annotation programs and a large global workforce.
Basic Qualifications

• 5+ years of team management experience
• 5+ years of program or project management experience
• Experience defining program requirements and using data and metrics to determine improvements
• Experience implementing repeatable processes and driving automation or standardization
• Experience managing, analyzing and communicating results to senior leadership
• Experience with tools/systems to analyze data including Excel, Access, SQL or other data management systems
• Experience managing programs across multiple geographies and cultures

Preferred Qualifications

• Experience in AI/ML operations, data annotation, or ML data quality.
• Lean Six Sigma Black Belt or equivalent process improvement certification
• Experience designing measurement or audit frameworks at scale
• Experience applying GenAI or LLM-based tools to improve operational metrics
• Experience operating as an independent quality assurance function alongside an operations organization

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