Director Quality Engineering

Director Of Quality Engineering

The Director of Quality Engineering leads the transformation of BSWH's quality assurance approach from primarily manual testing to a modern, automation-first quality engineering model. This role is accountable for establishing enterprise quality engineering practices that improve both product quality and speed of delivery across BSWH technology teams.

This leader owns quality engineering strategy, test automation, AI-enabled testing practices, quality metrics, release readiness, and the operating model for QA resources across BSWH. The role partners closely with Engineering, Product, Architecture, AI Foundation, Data & Analytics, Security, Privacy, Clinical, Operations, and vendor/partner teams to ensure that software and AI-enabled products are delivered safely, reliably, and efficiently.

The Director of Quality Engineering is responsible for building scalable quality practices that support modern engineering delivery, including shift-left testing, automated regression, API and UI automation, quality gates, performance testing, production validation, AI evaluation support, and continuous improvement. This role is a critical enabler of delivery velocity, product reliability, and customer trust.

This position can be based in our administrative building in Dallas, Texas or mostly remote with some travel required.

Essential Functions Of The Role

Quality Engineering Strategy & Transformation - Define and lead the enterprise quality engineering strategy for BSWH, shifting the organization from traditional manual QA toward automation-first, engineering-integrated, and AI-enabled quality practices.

Test Automation & AI-Enabled Testing - Lead the design and implementation of scalable test automation frameworks across API, UI, integration, regression, performance, accessibility, and end-to-end testing.

AI Quality & Evaluation Partnership - Partner with AI Architecture, AI Foundation, Engineering, Product, and Data teams to define quality practices for AI-enabled and agentic systems.

Release Quality, Reliability & Operational Readiness - Define release-readiness standards, quality gates, defect triage processes, regression expectations, test evidence requirements, and production validation practices.

Enterprise QA Operating Model & Talent Leadership - Oversee QA resources across BSWH and establish a consistent operating model for quality engineering roles, responsibilities, standards, and engagement with product and engineering teams.

Cross-Functional Partnership & Governance - Partner with Product, Engineering, Architecture, Security, Privacy, Compliance, Clinical, Data, Operations, and vendor teams to ensure quality expectations are defined early and embedded throughout delivery.

Key Success Factors

- Proven ability to lead quality engineering transformation from manual testing-heavy models to automation-first, engineering-integrated quality practices.

- Deep expertise in test automation strategy, tooling, framework design, CI/CD integration, quality metrics, release gates, and scalable QA operating models.

- Strong understanding of modern software delivery practices, including agile delivery, DevSecOps, shift-left testing, automated regression, API testing, UI testing, performance testing, and production validation.

- Ability to apply AI and automation to improve QA productivity, expand test coverage, reduce cycle time, and increase release confidence.

- Strong understanding of quality challenges for AI-enabled products, including testing expected behavior, evaluation criteria, guardrails, traceability, safety, and regression risk.

- Demonstrated ability to influence engineering, product, architecture, operations, security, and business stakeholders around common quality standards and delivery objectives.

- Strong talent leadership, including building, coaching, upskilling, and operating quality engineering teams across a complex enterprise environment.

- Ability to balance speed of delivery with reliability, compliance, customer trust, operational readiness, and long-term maintainability.

- Comfort operating in regulated, high-trust, or mission-critical environments where quality, safety, privacy, auditability, and reliability are essential.

- Strong communication and change-management skills, with the ability to shift organizational habits and expectations around quality ownership.

Preferred Qualifications

Education - Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related technical field. Master's degree preferred.

Experience - 15–18+ years of technology, software quality, quality engineering, test automation, software engineering, or related technology delivery experience. 7–10+ years of QA, quality engineering, automation, or engineering leadership experience.

Required Technical Expertise - Strong technical foundation in software quality engineering, test automation, application delivery, API testing, integration testing, UI testing, and release validation.