Director of Quality Engineering

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Director of Quality Engineering

Location: Fully Remote – U.S. Travel: Occasional travel to Dallas, TX, potentially once per quarter Compensation: $245,000-$270,000 base + 20% annual bonus Benefits: Healthcare + 401(k) Work Authorization: U.S. Citizens and Green Card holders only – no sponsorship

Candidates cannot currently reside in California, New York, Hawaii, North Dakota, Oregon, Rhode Island, Washington, or Wyoming.

About the Company

A large, mission-driven healthcare organization is investing heavily in modern engineering, automation, AI, and customer-facing digital experiences.

Operating at significant enterprise scale, the organization is accelerating its technology strategy and building modern capabilities across software engineering, data, AI, and digital products.

As engineering velocity increases, leadership is rethinking how quality is built into the software development lifecycle. The organization is now establishing a modern, automation-first Quality Engineering function capable of supporting both traditional software and the next generation of AI-enabled products.

About the Role

The Director of Quality Engineering will lead the transformation of an established, predominantly manual QA environment into a modern, automation-first Quality Engineering organization.

This is a true build opportunity.

Today, an existing QA team supports approximately 25 development teams, but there is no dedicated SDET function. The incoming Director will own the existing QA organization while building the technical capabilities, automation frameworks, SDET talent, standards, tooling, and operating model required for the future.

The immediate priority is establishing scalable deterministic automation across API, UI, integration, regression, performance, accessibility, and end-to-end testing while embedding quality directly into CI/CD and engineering workflows.

Longer term, the organization has an ambitious vision for AI-enabled and agentic testing-moving toward intelligent systems capable of generating tests, identifying defects, selecting regression coverage, and eventually executing increasingly complex testing workflows based on intent.

The successful candidate will be a builder who has transformed Quality Engineering before and is excited by the opportunity to create the strategy rather than inherit one.

Key Responsibilities

Define and execute the enterprise Quality Engineering strategy

Lead the transformation from manual-heavy QA toward an automation-first engineering model

Build a multi-year roadmap across automation, tooling, talent, metrics, and operating model modernization

Establish and scale a dedicated SDET and test automation capability

Lead the existing QA organization through its transition toward a more technical, automation-oriented model

Design scalable automation frameworks across API, UI, integration, regression, performance, accessibility, and end-to-end testing

Embed automated testing into CI/CD pipelines, development workflows, and release gates

Establish shift-left testing practices and reduce reliance on late-stage manual validation

Define enterprise standards for quality gates, release readiness, regression testing, defect triage, and production validation

Establish meaningful metrics around automation coverage, defect leakage, test effectiveness, release predictability, and production stability

Introduce AI-enabled approaches to test generation, maintenance, defect analysis, regression selection, and synthetic data

Partner with Engineering, Product, Architecture, Security, Data, AI, and Operations teams

Establish evaluation and quality practices for AI-enabled and agentic systems

Support validation of AI behavior, guardrails, traceability, safety, errors, fallback behavior, and human-in-the-loop workflows

Build, coach, and develop technical Quality Engineering talent

Must Haves

15+ years of experience across Quality Engineering, software quality, test automation, Software Engineering, or related technology delivery

7+ years of Quality Engineering, SDET, automation, QA, or engineering leadership

Proven experience transforming manual QA environments into automation-first Quality Engineering organizations

Experience building or substantially scaling test automation capabilities

Experience leading technical Quality Engineering, SDET, or engineering-adjacent teams

Deep understanding of modern test automation architecture and frameworks

Strong experience across API, UI, integration, regression, performance, and end-to-end testing

Experience embedding automated testing into CI/CD pipelines and release gates

Strong understanding of shift-left testing and engineering-owned quality

Experience defining quality gates, release-readiness standards, automation metrics, and testing strategy

Strong understanding of modern software engineering, Agile, CI/CD, and DevSecOps

Experience leading significant technical and organizational transformation

Ability to influence Engineering, Product, Architecture, Security, Operations, and executive stakeholders

Bachelor’s degree in Computer Science, Engineering, Information Systems, or another related technical discipline

AI & Next-Generation Quality Engineering

The strongest candidates will bring a point of view on where Quality Engineering is heading-not simply how testing has traditionally been done.

Experience or strong technical exposure in areas such as the following will stand out:

AI-assisted test generation and maintenance

Intelligent regression selection

AI-assisted defect analysis

Synthetic test data

AI evaluation frameworks

GenAI and conversational-system testing

Expected-behavior and guardrail validation

Hallucination and error detection

Human-in-the-loop validation

Agentic or intent-based testing

Automated monitoring and feedback loops for AI systems

The longer-term objective is not simply to automate manual test cases. It is to create a Quality Engineering capability capable of supporting increasingly intelligent and autonomous software systems.

Nice to Have

Playwright, Maestro, or comparable modern automation frameworks

Experience building an SDET organization from the ground up

Experience transforming an established manual QA workforce

AI, GenAI, machine learning, or agentic-system testing experience

Experience with customer-facing or mission-critical digital products

Healthcare or health technology experience

Financial services, life sciences, or another regulated/high-trust industry

Experience managing vendor, partner, or distributed QA resources

Master’s degree in a relevant technical discipline

Healthcare experience is valuable but is not the primary requirement for this search. Deep automation expertise and experience building technical Quality Engineering capabilities are significantly more important.

Why Join

Build an enterprise Quality Engineering capability from a near-blank slate

Define the automation strategy, frameworks, tooling, standards, and operating model

Establish a dedicated SDET capability

Transform an established manual QA environment rather than simply optimize an already mature automation program

Own both the technical strategy and organizational evolution

Build automation directly into modern engineering and CI/CD workflows

Help define how Quality Engineering evolves for GenAI and agentic systems

Work toward an ambitious longer-term vision for intent-based and agentic testing

Partner directly with senior Engineering, Product, Architecture, Data, and AI leaders

Work on customer-facing technology where quality and reliability have meaningful real-world impact

Fully remote with limited travel to Dallas, TX

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