AI Test Automation Engineer - Performance & API Focus Job at McKesson, Jacksonville, FL

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  • McKesson
  • Jacksonville, FL

Job Description

Position Summary

McKesson Corporation is seeking detail-oriented and technically proficient Quality Engineer with a strong background in test automation, continuous integration, API testing, performance validation, and AI-enhanced quality practices.

With 4+ years of experience, the ideal candidate will play a key role in ensuring the reliability, scalability, and performance of our software products through intelligent and automated testing strategies.

Key Responsibilities

  • Design, develop, and maintain automated test frameworks using tools such as Selenium, Playwright, or similar.
  • Integrate automated tests into CI/CD pipelines using platforms like Jenkins, GitLab CI, Azure DevOps, etc.
  • Develop and execute API tests using tools like Postman, REST Assured, or SoapUI.
  • Conduct performance and load testing using tools such as JMeter, Gatling, NeoLoad or LoadRunner.
  • Collaborate with development, DevOps, and product teams to ensure quality is embedded throughout the software lifecycle.
  • Leverage AI/ML tools to enhance test coverage, defect prediction, and intelligent automation.
  • Manage test cases, execution, and reporting using test management tools like Jira, TestRail, or Zephyr.
  • Analyze test results, identify root causes, and contribute to continuous improvement of testing processes.

Minimum Qualifications

Typically requires 4+ years of relevant experience.

Critical Skills

  • Strong understanding of API testing, performance testing, and test automation frameworks.
  • Proficiency in programming languages such as Java, Python, or JavaScript.
  • Hands-on experience with CI/CD tools and DevOps practices.
  • Experience implementing AI/ML concepts and their application in quality engineering.
  • Excellent analytical, problem-solving, and communication skills.

Preferred Attributes

  • Experience in healthcare or supply chain domain.
  • Experience with containerization (Docker, Kubernetes).
  • Exposure to MLOps and AI model validation.

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