Director, Quality Intelligence Programs

## About the team

The Quality Intelligence team is a dynamic group of program managers, insights managers, and development leaders who collaborate cross-functionally to drive measurable behavior change and positive customer outcomes. The team sits within the Customer Experience Operations organization, and partners closely with other shared service groups, including but not limited to Engineering, Data & Analytics, Operations Strategy, and Frontline Leadership.
Right now, the team is at a pivotal stage of evolution, responsible for transforming quality from a monitoring function into an intelligence engine that captures and interprets customer interactions, integrates with enterprise systems, and delivers real-time, actionable insights. This transformation requires rethinking governance, redefining how insights flow into coaching and product feedback loops, and embedding quality intelligence directly into frontline workflows.
Our mission is to build a trusted quality intelligence program that not only measures performance, but actively shapes how we learn, improve, and deliver value to customers at scale.## About the role

The Director, Quality Intelligence Programs is responsible for building and operationalizing quality as a scalable, intelligence-driven capability that measurably improves frontline behavior, customer outcomes, and enterprise decision-making. This role leads the end-to-end program that governs how quality data is generated, integrated, interpreted, and activated across Customer Experience Operations (CXO). This leader owns both the implementation and modernization of our AI-powered quality intelligence platform and the programmatic translation of quality insights into action: coaching, training, automation, and product feedback loops.

They will move quality from a retrospective scoring function to a continuously evolving system that informs real-time interventions and long-term CX strategy. Operating at the intersection of technology, operations, and change management, this role ensures quality intelligence is embedded in workflows, enterprise data systems, and executive decision-making. Success requires strong program leadership, technical fluency, cross-functional influence, and a relentless focus on execution and adoption.

This individual will know they are successful with:
1) the successful integration of quality data into a customer intelligence ecosystem;
2) sustained improvement in automated insight accuracy;
3) demonstrated linkage between quality insights and measurable improvements in CSAT; and
4) executive confidence in quality monitoring as a core data asset supporting customer strategy.
** Key Responsibilities
*** Lead the Quality Intelligence function:
Define and execute the long-term vision for quality monitoring as a data intelligence function, not a manual evaluation process.
* Establish governance framework for transcription, sentiment detection, and behavioral analytics

Ensure the platform continuously evolves in accuracy, coverage, and insight depth through feedback loops and data calibration.
* Govern Quality Data

Infrastructure: Own the integrity and reliability of all quality-related data flowing into the central customer intelligence base, ensuring alignment with data standards.
* Partner with engineering and Analytics to integrate quality signals with CSAT and operational metrics.
* Ensure bi-directional data sharing between Quality platform, knowledge base, and CXO data that supports enablement, product feedback, and automation initiatives.
* Enable Actionable Insight & Intervention:
Translate model outputs into insights that inform coaching, training, and product improvement.  Build closed-loop systems where quality insights automatically generate intervention recommendations or learning pathways for frontline teams.
* Technical Ownership &

Innovation: Oversee configuration and management of speech and text analytics, including taxonomy evolution and sentiment weighting.
* Lead efforts to benchmark AI model accuracy and drive improvement.
* Ensure alignment with broader enterprise data architecture, API frameworks, ML governance standards, and responsible AI…