Senior Program Manager

we are looking for a Senior Program Manager.
The Senior Program Manager, Quality Engineering is a pivotal role within our R&D organization, responsible for driving governance, process excellence, and strategic. This person leads cross-suite integration programs, spearheads AI tools adoption, and owns quality and performance improvement initiatives - acting as the connective tissue between QA, R&D, Product, and Release teams. The right candidate brings both rigor and vision: able to standardize how we deliver quality software while actively pushing the organization forward through innovation and tooling.
How will you make an impact?
SDLC Governance & Quality Process
Own and drive governance across Quality Engineering - from sprint planning through release sign-off.
Define and maintain quality process standards, ensuring consistent adoption across cross-functional R&D teams.
Track and report on quality KPIs, test coverage, defect trends, and release readiness to stakeholders and leadership.
Identify process gaps, risks, and blockers; drive course corrections to keep quality milestones on track.
Coordinate with Release Management to align QA sign-off gates with deployment schedules.
Cross-Suite Integration Programs
Lead end-to-end cross-suite integration programs spanning multiple product lines, R&D teams, and geographies.
Coordinate cross-functional dependencies, align timelines, and ensure quality standards are upheld across all integrated components.
Serve as the primary integration point between QA, Architecture, Product Management, and Engineering for complex multi-team deliverables.
Articulate integration status, risks, and plans with accuracy to stakeholders at all levels - from engineers to executive leadership.
AI Tools Adoption
Lead the evaluation, rollout, and adoption of AI-powered tools within the Quality organization.
Partner with Engineering and tooling owners to define AI tool integration standards, governance policies, and success metrics.
Champion a culture of continuous learning and experimentation with emerging AI capabilities across QA and SDLC workflows.
Measure and communicate the impact of AI tooling on quality outcomes, developer productivity, and time-to-delivery.
Quality & Performance Improvement Programs
Define, own, and execute ongoing quality improvement programs targeting defect escape rates, test coverage, and release predictability.
Drive performance improvement initiatives across the QA function through data-driven insights, retrospectives, and process redesign.
Partner with tooling owners (CI/CD, test automation, static analysis) to ensure pipeline quality gates are well-governed and continuously optimized.