Engineering Program Manager, Quality Assurance - Customer Systems

The Program Manager - Quality Assurance will Leads end-to-end quality execution and program governance for large scale software development programs. This is a hands-on, execution-focused role that requires close partnership with Engineering, Product, Operations, and Vendor teams to ensure quality, readiness, and smooth delivery across all migration phases. Leveraging GenAI to gain efficiencies in quality management.\\nWe are looking for a Program Manager who brings practical experience in QA, test automation, and release management - including hands-on use of GenAI tools to accelerate and enhance quality workflows. In this role, you will coordinate and execute testing activities, manage risks and dependencies, and drive release readiness across multiple work streams. You thrive in fast-paced, complex environments and are passionate about delivering high-quality customer experiences.

Partner with Engineering and Product to define test plans, test scope, and acceptance criteria for migration features and integrations.\nCoordinate and track functional, integration, regression, and business testing across teams. Ensure test environments, data, and test cases are prepared and validated ahead of each testing cycle.\nDrive day-to-day execution across cross-functional teams including Engineering, Contact Center Operations, Infrastructure, Security, SRE, Architects, Platform Teams, DevOps, Vendors.\n\nIdentify and track dependencies, risks, and blockers; escalate proactively with clear context and mitigation options.\nAlign QA timelines with release plans, pilots, and phased rollouts.\nFacilitate defect triage, track resolution progress, and ensure closure prior to release milestones.\nMaintain clear visibility into QA readiness, test coverage, and open risks.\nSupport go/no-go decisions with structured and well-documented readiness assessments.\nDeliver regular, concise status updates to both technical and business stakeholders.\n\nTranslate QA risks and findings into business impact and customer experience implications.\nServe as the coordination point between internal teams and external vendors throughout testing cycles.\nContinuously improve QA processes, templates, and reporting practices across the program.\nDrive the adoption of test automation and structured release governance where applicable.\nLeverage GenAI tools to auto-generate test plans, test cases, and acceptance criteria from product requirements, design specs, and user stories\n\nUse GenAI to perform gap analysis on existing test coverage by analyzing requirements documents and surfacing untested scenarios\nAutomate the generation of status reports and dashboards by feeding GenAI structured test run data and defect metrics\nApply GenAI tools to triage and classify incoming defects - auto-tagging by severity, component, or feature area to reduce manual overhead\nUse GenAI to analyze retrospective data and surface recurring process bottlenecks or quality escapes across sprints and releases\nApply GenAI to benchmark QA process maturity by comparing current workflows against industry best practices\nLeverage GenAI to help design and refine QA workflows, checklist templates, and team onboarding guides\nEvaluate and champion GenAI-assisted test automation tools that can generate and maintain automated test scripts from natural language descriptions\n

Experience with platform migrations, system integrations, or SaaS implementations.\nProficiency with QA tools such as Selenium, Playwright, JMeter, RestAssured and a working understanding of test automation concepts.\nExperience collaborating with vendors or external implementation partners \nExperience applying GenAI tools and AI-assisted workflows within Quality Engineering or SDLC processes.\nStrong organizational, communication, and execution skills.

Experience with platform migrations, system integrations, or SaaS implementations.\nProficiency with QA tools such as Selenium, Playwright, JMeter, RestAssured and a working understanding of test automation concepts.\nExperience collaborating with vendors or external implementation partners \nExperience applying GenAI tools and AI-assisted workflows within Quality Engineering or SDLC processes.\n