CX Quality Assurance Lead

About the Role

Headway is looking for an experienced QA Lead to evolve how quality works across our CX organization as we move from manual evaluation to a system that generates insights continuously, surfaces behavioral trends at scale, and drives the decisions that make our agents better and our customers better served.

This is a customer support quality assurance role focused on agent evaluation, conversation analytics, and AI-powered quality measurement — not software testing, test automation, or CI/CD engineering

You'll be joining the Agent Success team within Customer Experience, a function focused on making our CX agents more effective, more consistent, and better supported. QA is in active evolution here; we're moving from a manual, sampling-based model to a specialized, insight-driven system, and the people we hire will have a direct hand in building it. Your role will have real ownership over a defined area of the QA program — calibration and framework governance, AI-powered analytics and insights, or vendor and partner quality oversight, depending on role fit.

This isn't a traditional QA role where you spend your days manually grading interactions. You'll design the systems, analyze the signals, and surface the patterns that change how we operate, with clear ownership over outcomes.

Your work will give CX leadership consistent, reliable visibility into performance, process, and operations — and the context to act on what they find.

You will:

• Own a defined area of the QA program end-to-end (calibration and rubric governance, AI-powered analytics, or partner quality) and drive it from signal to action
• Set quality standards and rubric logic for your area; ensure consistent application across channels and partners and recommend framework updates based on outcomes
• Configure and continuously improve AI-QA tooling (ObserveAI or similar) with set scoring logic, monitoring accuracy, and ensuring the platform delivers consistent, actionable output
• Build automation into QA workflows to reduce manual overhead and expand coverage; establish AI-assisted processes for status updates, reporting, and initiative recaps
• Analyze quality and conversation data to surface DSAT drivers, behavioral trends, escalation patterns, and workflow gaps by going beyond what happened to understand why
• Design and maintain dashboards that track key quality metrics; translate findings into clear operational recommendations for CX leadership
• Produce structured insight reports (clear signal, root cause, recommended action) and ensure findings flow into training, content, coaching, and product decisions