AI Transformation Lead - Quality Assurance and Customer Experience

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in a technical project management or a customer-facing role.
  

Preferred qualifications:

• Master’s degree in Business, Statistics, Mathematics, Economics, Engineering or Applied Science, or a related field.
• 10 years of experience leading scaled operations/Managed Service Providers (MSPs).
• Experience in process optimization methodologies (e.g., Lean, Six Sigma, Value Stream Mapping) to identify bottlenecks and reduce customer effort.
• Ability to drive AI quality assurance and operational automation through prompt engineering, code-based workflow integrations (e.g., using Python, Java, Apps Script, or similar), and the development of Large Language Model (LLM)-powered agents and SQL-backed reporting dashboards.
• Familiarity with digital advertising technology, Google's sellside products (Google Ad Manager, AdMob, AdSense), or technical support environments.

About the job

Google creates products and services that make the world a better place, and gTech’s role is to help bring them to life. Our teams of trusted advisors support customers globally. Our solutions are rooted in our technical skill, product expertise, and a thorough understanding of our customers’ complex needs. Whether the answer is a bespoke solution to solve a unique problem, or a new tool that can scale across Google, everything we do aims to ensure our customers benefit from the full potential of Google products.

To learn more about gTech, check out our video.

Responsibilities

• Lead the design, evolution, and oversight of the Sellside Quality Framework, aligning audit criteria with the end-to-end publisher journey.
• Transform traditional manual auditing workflows to AI-powered, continuous baseline audits augmented by targeted human calibration and partner with technical teams to design, test, and implement agentic quality tools to scale audit coverage to 100%.
• Maximize AI reliability and accuracy by designing, testing, and relentlessly optimizing complex system prompts that successfully minimize hallucinations and efficiently handle challenging operational edge cases.
• Drive improvement of partner experiences, identifying areas of opportunity to streamline processes, content and strategy, implement updates etc.
• Manage daily operational activities (reporting, root cause analysis, and feedback loops) required to enforce quality standards and accountability across global vendor operations and Managed Service Providers (MSPs).