AVP, Quality Assurance

Leads the enterprise Quality Assurance (QA) strategy for the Information Technology organization, ensuring the delivery of high-quality, reliable, and scalable software solutions. This role establishes a forward‑looking quality engineering vision that integrates automation, Dev Ops practices, and emerging AI capabilities into the software development lifecycle. The AVP drives transformation from traditional testing to a modern, automation‑first and AI‑enabled quality engineering model, embedding quality at every stage of the delivery pipeline.

This includes advancing continuous testing, improving speed to market, and reducing production risk. This leader partners with Engineering, Architecture, Product, and Operations to institutionalize quality as a shared responsibility, align QA with enterprise priorities, and influence strategic technology decisions. The role oversees internal teams and external partners, ensuring delivery excellence, cost efficiency, and continuous improvement across the QA function.

• Defines and leads the enterprise QA and Quality Engineering strategy, aligning with IT and business priorities.
• Establishes a future‑state vision for QA, transitioning from manual testing to automation‑led, Dev Ops‑integrated delivery models.
• Champions a shift‑left, quality‑first culture across the software development lifecycle.
• Drives measurable improvements in defect reduction, cycle time, and production stability.

• Leads the design and implementation of end‑to‑end test automation frameworks integrated within CI/CD pipelines.
• Ensures continuous testing practices are embedded into Dev Ops workflows to enable faster, higher‑quality releases.
• Partners with Engineering to standardize automation tools, environments, and pipeline integration patterns.
• Establishes KPIs and reporting for automation coverage, pipeline efficiency, and release quality.

• Defines and advances the adoption of AI and machine learning capabilities within QA, including intelligent test generation, predictive defect analysis, and self‑healing automation.
• Partners with enterprise AI initiatives to embed AI into testing strategies and tooling.
• Evaluates and pilots emerging AI‑driven QA tools to improve efficiency, accuracy, and scalability.

• Establishes enterprise standards for quality governance, test methodologies, and compliance.
• Provides executive‑level oversight of quality risk management, including defect trends, test coverage gaps, and release readiness.
• Ensures alignment with regulatory, audit, and SOX/ITGC requirements.

• Establishes and leads strategic partnerships across Engineering (Dev Ops), Operations, and Business teams to ensure quality is embedded across the full software lifecycle.
• Dev Ops / Engineering Partnership (Quality in Delivery):
  • Partners with Engineering and Dev Ops teams to embed quality directly into the development lifecycle, including integration of automated testing into CI/CD pipelines, implementation of continuous testing practices, and alignment on engineering standards that promote quality, speed, and stability.
• Operations Partnership (Production Quality & Stability):
  • Collaborates with Operations to define, monitor, and continuously improve production quality metrics, including defect leakage, incident trends, and system stability. Ensures alignment on production readiness, release quality gates, and post‑release performance, supporting seamless migration to production and ongoing reliability.
• Business & UAT Partnership (Customer & Business Validation):
  • Partners with business stakeholders to strengthen User Acceptance Testing (UAT) practices, ensuring solutions meet business requirements and deliver intended outcomes. Establishes clear ownership, governance, and processes for business validation, defect triage, and release acceptance criteria.
• Drives end‑to‑end alignment across these functions to ensure quality accountability is shared, measurable, and consistently executed across the…