Team Lead - Quality Assurance, Support Excellence

Adyen·Chicago·onsite
crypto:applicationengineeringIC5Support
Compensation
Not disclosed
This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Team Lead - Quality Assurance, Support Excellence Quality Assurance is a critical function within Support, ensuring consistent, high-quality experiences for both our customers and the Support agents who serve them. As our products and customer base grow in scale and complexity, QA plays a key role in delivering accurate, compliant support that delivers great merchant experience, while equipping agents with clear standards and actionable feedback to grow. At the same time, advancements in AI are reshaping how quality is measured and improved, and AI will play a central part of this role and the experience we’re seeking in the candidate we hire. We are building an AI-first QA model that enhances how we evaluate interactions, generate insights, and drive iterative improvements across the customer journey. As the Team Lead for Support QA, you will define and execute this vision, directly improving key Support metrics such as CSAT and NPS and drive down escalations and re-opened cases. You will lead a small, high-impact team and partner cross-functionally to ensure quality is consistently measured, trusted, and drives meaningful improvements. What You’ll Do Define and own the long-term QA vision, with a focus on the transition from manual QA to AI-led evaluation models Define “what great looks like” by building and evolving QA framewor