Director of Quality Engineering

Acumen Fiscal Agent; Mesa (AZ); Sur place; USD 180 000 - 240 000; Plein temps

Résumé du poste

Acumen Fiscal Agent seeks a Director of Quality Engineering to lead the evolution from QA to a modern Quality Engineering capability, boosting release confidence, velocity, automation, and shared accountability across Product and Engineering.

You will define strategy, embed quality across discovery to release, build automation across unit/API/integration/testing integrated into CI/CD, and apply AI tooling. Collaboration with Engineering, Product, Cloud & Platform, and Security is essential.

Qualifications

• 10+ years of progressive software engineering, software quality engineering, test automation, or related experience, including significant leadership responsibility.
• Demonstrated experience transforming manual or downstream QA into an engineering-led, automation-oriented quality capability.
• Strong technical depth in automated testing architectures, APIs, integration testing, CI/CD, cloud applications, and modern test frameworks.
• Experience developing risk-based testing strategies for complex, integrated, or high-consequence software systems.
• Strong understanding of Agile/software-development practices and shared accountability for quality.
• High proficiency with modern AI tools and frontier models, with demonstrated ability to apply AI safely and productively to testing, automation, analysis, engineering workflows, and team productivity.
• Experience in healthcare, financial services, regulated technology, or another high-consequence environment preferred.
• Bachelor's degree in computer science, engineering, or related discipline, or equivalent relevant experience.

Responsabilités

• Define and execute the enterprise Quality Engineering strategy, operating model, standards, and roadmap.
• Embed quality throughout discovery, requirements, design, development, and release processes, including strong acceptance criteria and early risk identification.
• Establish a risk-based quality framework that aligns testing depth and methods to business impact, technical complexity, customer workflows, integrations, and production risk.
• Build an automation-first testing capability across unit, API, integration, regression, performance, and end-to-end testing, integrated directly into CI/CD pipelines.
• Apply AI and agentic tooling to accelerate test generation, exploratory testing, regression analysis, defect investigation, test maintenance, and release-readiness assessment.
• Establish meaningful quality gates, release-confidence criteria, metrics, and feedback loops spanning testing, escaped defects, production incidents, and corrective action.
• Partner with Software Engineering, Product, Cloud & Platform Engineering, and Information Security to improve testability, resilience, observability, and secure delivery.
• Develop the internal QE team, retain critical domain knowledge, establish engineering standards and career expectations, and use contractors strategically.

Connaissances

Quality Engineering leadership

Automation testing

CI/CD

AI tooling usage

Agile practices

Team leadership

Formation

Bachelor's degree in computer science or related

Outils

CI/CD tools

Automation frameworks

AI tooling

Description du poste

Position Summary

Lead the evolution of software quality from traditional QA into a modern Quality Engineering capability that improves release confidence, development velocity, automation, and shared accountability for quality across Product and Engineering.

Director, Quality Engineering

Lead the evolution of software quality from traditional QA into a modern Quality Engineering capability that improves release confidence, development velocity, automation, and shared accountability for quality across Product and Engineering.

Key Duties & Responsibilities

• Define and execute the enterprise Quality Engineering strategy, operating model, standards, and roadmap.
• Embed quality throughout discovery, requirements, design, development, and release processes, including strong acceptance criteria and early risk identification.
• Establish a risk-based quality framework that aligns testing depth and methods to business impact, technical complexity, customer workflows, integrations, and production risk.
• Build an automation-first testing capability across unit, API, integration, regression, performance, and end-to-end testing, integrated directly into CI/CD pipelines.
• Apply AI and agentic tooling to accelerate test generation, exploratory testing, regression analysis, defect investigation, test maintenance, and release-readiness assessment.
• Establish meaningful quality gates, release-confidence criteria, metrics, and feedback loops spanning testing, escaped defects, production incidents, and corrective action.
• Partner with Software Engineering, Product, Cloud & Platform Engineering, and Information Security to improve testability, resilience, observability, and secure delivery.
• Develop the internal QE team, retain critical domain knowledge, establish engineering standards and career expectations, and use contractors strategically.

Background & Qualifications

• 10+ years of progressive software engineering, software quality engineering, test automation, or related experience, including significant leadership responsibility.
• Demonstrated experience transforming manual or downstream QA into an engineering-led, automation-oriented quality capability.
• Strong technical depth in automated testing architectures, APIs, integration testing, CI/CD, cloud applications, and modern test frameworks.
• Experience developing risk-based testing strategies for complex, integrated, or high-consequence software systems.
• Strong understanding of Agile/software-development practices and shared accountability for quality.
• High proficiency with modern AI tools and frontier models, with demonstrated ability to apply AI safely and productively to testing, automation, analysis, engineering workflows, and team productivity.
• Experience in healthcare, financial services, regulated technology, or another high-consequence environment preferred.
• Bachelor's degree in computer science, engineering, or related discipline, or equivalent relevant experience.