Purpose of the Role
The Quality Analyst Manager (AI & Customer Experience) is a strategic leadership role responsible for driving quality assurance excellence across customer interactions handled by both human agents and AI-powered systems. The role combines people leadership, operational oversight, data-driven improvement, and governance to ensure exceptional customer experience, compliance, and continuous process optimization.
This position manages a team Quality Analysts, establishes QA frameworks, monitors performance trends, and leads initiatives to improve service quality, AI interaction accuracy, and operational effectiveness.
The ideal candidate is a strong people manager with deep expertise in contact center quality assurance, coaching, analytics, and (emerging AI-assisted customer service environments), is an added advantage.
Key Focus Areas
Lead and develop the QA function
- Manage QA analysts, set quality standards, and drive a high-performance culture.
Oversee AI call quality assurance
- Evaluate AI-handled interactions for accuracy, tone, compliance, escalation handling, and customer satisfaction.
- Work with AI QA portal to set variables, check results, flag any process gaps and own the entire ecosystem process from beginning the end.
Drive operational improvement
- Use QA insights and analytics to identify trends, reduce defects, and improve customer experience outcomes.
Ensure governance and compliance
- Maintain adherence to company policies, regulatory requirements, and quality standards across all customer interactions.
Partner cross-functionally
- Collaborate with Operations, Training, Product, and AI/Automation teams to improve processes and performance.
Key Responsibilities
Leadership & Team Management
- Lead, mentor, and develop QA analysts.
- Set performance goals, conduct regular coaching sessions, and manage career development plans.
- Build a culture of accountability, continuous learning, and customer-centric quality excellence.
- Manage staffing, scheduling, and workload distribution within the QA function.
Quality Strategy & Governance
- Design and maintain the QA framework, scorecards, calibration processes, and reporting standards.
- Ensure consistency and fairness in evaluations across human and AI-handled interactions.
- Lead calibration sessions with Operations and align on quality expectations.
- Monitor compliance with regulatory, security, and company policies.
AI Interaction Quality Oversight
- Establish QA standards for AI-handled calls, chats, and automated interactions.
- Review AI interactions for accuracy, empathy, tone, intent recognition, resolution quality, and escalation of appropriateness.
- Identify AI performance gaps, recurring customer pain points, and automation risks.
- Partner with AI/Product teams to improve conversational flows, knowledge accuracy, and automation effectiveness.
- Track AI-specific quality metrics and offer improvement feedback where necessary.
Performance Monitoring & Reporting
- Analyze QA data to identify trends, root causes, and opportunities for improvement.
- Prepare and present quality reports, dashboards, and actionable insights to senior leadership.
- Measure the impact of coaching, training, and process changes on performance outcomes.
- Drive initiatives to improve CSAT, FCR, compliance, and overall service quality.
Training & Continuous Improvement
- Collaborate with Training teams to design targeted learning programs based on QA findings.
- Develop best practices, knowledge-sharing sessions, and quality improvement initiatives.
- Champion continuous improvement methodologies to enhance efficiency and customer experience.
