AVP, Quality Assurance

American Equity•Des Moines, IA

1d•Onsite

About The Position

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, DevOps 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.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field, or an equivalent combination of education and experience; advanced degree (MBA, MIS, or similar) preferred.
Minimum of 10+ years of experience in Quality Assurance, Quality Engineering, or Software Delivery, including 6+ years in progressive leadership roles overseeing enterprise-scale QA functions.
Demonstrated experience defining and executing enterprise QA or Quality Engineering strategy, including transformation from traditional testing to automation-led delivery models.
Proven leadership in designing and scaling test automation frameworks and embedding continuous testing within CI/CD pipelines (DevOps environments).
Hands-on experience or leadership oversight in modern QA tooling ecosystems (e.g., automation frameworks, test management tools, DevOps platforms, and pipeline integrations).
Experience leveraging or implementing AI/ML capabilities in QA, such as intelligent test generation, predictive analytics, or workflow optimization, strongly preferred.
Proven success leading large, distributed teams (onshore/offshore, vendor and managed service models), including contract negotiation and vendor performance management.
Strong experience partnering with Engineering, Architecture, and Product leadership to influence delivery models, engineering practices, and quality outcomes.
Experience operating within regulated environments, with knowledge of audit, risk management, and SOX/ITGC controls preferred.
Demonstrated ability to translate business strategy into technology execution, with a focus on improving speed, quality, and reliability of software delivery.
Ability to define and execute enterprise-wide QA and Quality Engineering strategies aligned to business and IT objectives
Strong executive presence with the ability to influence senior leadership, architecture, and engineering decisions
Demonstrated ability to translate business priorities into scalable, technology-enabled solutions
Deep expertise in modern Quality Engineering practices, including automation-first testing, shift-left principles, and continuous testing
Strong knowledge of CI/CD pipelines and DevOps frameworks, with the ability to embed QA seamlessly into delivery workflows
Experience designing and scaling test automation frameworks across complex, integrated systems
Understanding of test environment management, data strategy, and pipeline optimization
Knowledge of AI/ML capabilities in QA, including intelligent test automation, predictive analytics, and self-healing frameworks
Ability to evaluate, pilot, and scale emerging QA and AI-driven technologies
Strong learning agility to stay ahead of rapidly evolving technology trends
Strong financial acumen with ability to optimize QA investments, balancing cost, quality, and speed
Experience managing vendor partnerships and managed services, including performance governance and contract accountability
Ability to drive operational efficiency and measurable quality outcomes
Advanced analytical and problem-solving skills with ability to translate data into actionable insights
Strong understanding of risk management, defect trends, and release readiness indicators
Knowledge of regulatory, audit, and SOX/ITGC requirements and how they apply to QA practices
Proven ability to build, lead, and scale high-performing, multi-level teams across onshore/offshore models
Strong change leadership capability, driving adoption of new tools, processes, and ways of working
Ability to foster a culture of accountability, innovation, and continuous improvement
Exceptional communication and storytelling skills, with the ability to convey complex technical concepts to executive audiences
Strong collaboration skills across Product, Engineering, Architecture, and Operations
Ability to navigate ambiguity and align diverse stakeholders toward common outcomes

Responsibilities

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, DevOps-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 DevOps 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 (DevOps), Operations, and Business teams to ensure quality is embedded across the full software lifecycle.
Partners with Engineering and DevOps 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.
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.
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 organization.
Oversee QA vendor strategy, including staff augmentation and managed service models.
Optimizes QA investment by balancing cost, quality, and delivery outcomes.
Manage contracts, performance metrics, and accountability for external partners.
Builds and leads a high-performing Quality Engineering organization, including managers and specialized QA roles.
Develops leadership capabilities and succession pipelines within QA.
Promotes a culture of innovation, accountability, and continuous improvement.
Leads organizational change to support modern QA practices and tools adoption.