AI-Driven Quality Engineer, Test Automation

Baylor Scott & White Health; Cheyenne (WY); On-site; USD 110,000 - 165,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Tuition Reimbursement

PTO

Job summary

Baylor Scott & White Health is seeking a Quality Engineer, AI & Test Automation to modernize quality practices. The role builds automated test suites for API, UI, and AI-enabled use cases, embeds quality in CI/CD, and collaborates with Product, Engineering, Data & Analytics, and Security teams to ensure reliable delivery.

Responsibilities include defining validation plans, metrics, and release-readiness, while advancing AI testing practices and responsible use of AI tools.

Qualifications

• Bachelor's degree in CS/Engineering or related field.
• 5–8+ years in quality engineering or test automation.
• Experience with API/web/mobile testing and CI/CD.
• Healthcare or regulated industry experience preferred but not required.

Responsibilities

• Develop test strategies, plans, acceptance criteria, and quality approaches with stakeholders.
• Translate requirements and APIs into clear test scenarios and validation plans.
• Identify risks early and recommend validation approaches including AI-specific methods.
• Provide release-readiness input based on test evidence and quality metrics.
• Design, build, and maintain automated test suites for API/UI/integration.
• Integrate tests into CI/CD pipelines for earlier quality signals.

Skills

Automation testing

API testing

CI/CD integration

Data validation

AI testing

Defect triage

Quality metrics

SDET experience

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or related field

Equivalent combination of education and relevant technical experience

Tools

Playwright

Cypress

Selenium

PyTest

Postman

Job description

Baylor Scott & White Health is seeking a Quality Engineer, AI & Test Automation to modernize quality practices. The role builds automated test suites for API, UI, and AI-enabled use cases, embeds quality in CI/CD, and collaborates with Product, Engineering, Data & Analytics, and Security teams to ensure reliable delivery.

Responsibilities include defining validation plans, metrics, and release-readiness, while advancing AI testing practices and responsible use of AI tools.