Manager, Quality Engineering

About the Role

Nu Skin is modernizing how it builds and ships commerce, accounts, commissions and content experiences for customers and brand affiliates in dozens of markets. As we finish the global rollout of the Equinox commerce platform and migrate content to ContentStack, quality engineering is shifting from largely manual regression toward AI-assisted, automation-first testing that gives every team fast and trustworthy release confidence. The Manager, Quality Engineering leads the QA Platform team, a shared enabling team that serves all of Global Software Engineering. You will own the quality strategy, lead a blended team of employees and managed-service partners, and drive the adoption of AI in test design, execution, maintenance and reporting. You will partner closely with Engineering Managers, Architects, Product Owners and Program Managers, and report to the Sr. Director of Global Software Engineering.

What You Will Do

Lead the team and the strategy

• Lead, coach and grow QA managers, QA engineers and SDETs across employees and managed-service partners, including onshore and offshore teams; run regular 1:1s, set clear goals and measure results.
• Define and own the enterprise test strategy, quality standards, entry and exit criteria, and release-readiness evidence for web, mobile, API, integration and SAP-connected workloads.
• Manage partner relationships, statements of work, capacity and budget for external QA resources; hold partners to clear outcomes and KPIs.
• Establish and report quality KPIs to engineering and executive leadership: automation coverage, defect escape rate, flaky-test rate, cycle time, release confidence and cost of quality.

Drive AI-powered test automation

• Build and execute a roadmap to embed AI across the test lifecycle: generating test cases and test data from requirements and user stories, self-healing locators, intelligent test selection and prioritization, failure triage and root-cause clustering, and visual and exploratory testing.
• Evaluate, pilot and adopt AI testing tools and LLM-based agents, with clear build-versus-buy reasoning, security and data-privacy review, and measured return on investment.
• Use AI assistants to accelerate engineers' own work (code generation for test suites, refactoring, documentation) while maintaining human review and quality guardrails.
• Define how AI-generated tests and results are validated, audited and trusted, including guardrails against hallucinated or low-value tests.
• Reduce manual regression effort measurably, shifting capacity toward higher-value exploratory, performance, security and accessibility testing.

Build quality into delivery

• Own the shared automation platform and frameworks (such as Playwright and Appium), and integrate suites into GitLab CI/CD pipelines as automated quality gates.
• Embed quality engineers with stream and platform teams; promote shift-left practices, contract and API testing, and testable design with Architects and Engineering Managers.
• Maintain test management and quality reporting (such as TestLink, ReportPortal, SonarQube and Jira) so that evidence is consistent, searchable and audit-ready.
• Lead quality planning for major programs, including platform migrations, market launches and peak-season readiness, and coordinate UAT with business partners.
• Partner on defect management and incident reviews; turn recurring escapes into prevention.

What You Bring

Required

• 8+ years in software quality engineering, including 3+ years leading QA or SDET teams, preferably with distributed and vendor-supported teams.
• Hands-on experience designing and scaling test automation frameworks (UI, API, mobile) and integrating them into CI/CD.
• Demonstrated use of AI or machine learning to improve testing, such as AI-assisted test generation, self-healing automation, intelligent triage or LLM-based agents, with results you can quantify.
• Strong grasp of modern test strategy: test pyramid, risk-based testing, shift-left, performance and security testing basics.
• Experience in enterprise e-commerce, ERP or integration-heavy environments.
• Proven ability to manage budgets, vendor contracts and stakeholders, and to communicate clearly with engineers, product owners and senior leaders.
• Bachelor's degree in computer science, engineering or equivalent experience.

Preferred

• Experience with Playwright, Appium, GitLab CI, Jira, TestLink, ReportPortal and SonarQube, or comparable tools.
• Familiarity with SAP, commerce platforms (such as Equinox), headless CMS (such as ContentStack or AEM) and event-driven integration.
• Experience establishing governance for responsible AI use in engineering, including data handling and model risk.
• Experience working with teams in India and other global time zones; ISTQB or similar certification.

What Success Looks Like

• Within 90 days: assessed team capacity, partner contracts and automation coverage; named a 12-month quality and AI-automation roadmap with agreed KPIs.
• Within 6 months: at least one AI-assisted testing capability in production use with measured reduction in manual regression effort and flaky-test rate.
• Within 12 months: automated quality gates in the release pipelines of all stream teams, a trusted quality dashboard for leadership, and a stable, engaged QA team.