Quality Assurance Lead

Peraton is seeking a Quality Assurance Team Lead for the Department of Defense (DoD) DMDC's Enterprise Law Enforcement Support Services (ELEs2).  In this role, you will play a vital role in ensuring the accuracy, reliability, and performance of AI models and systems. This position is essential for maintaining the integrity of AI-driven products and services, contributing to the overall quality standards of this program. You will collaborate closely with all stakeholders to develop and implement robust strategies that validate AI functionalities and identify areas for improvement.

 What You’ll Do:

• Develop and execute comprehensive test plans for AI models.
• Implement automated testing frameworks to streamline validation processes.
• Analyze test results to identify and document defects.
• Collaborate with data scientists and machine learning engineers to enhance model performance.
• Contribute to the development of data quality metrics and monitoring systems.
• Participate in code reviews to improve development processes.
• Engage with product managers to ensure AI models meet user requirements.

Required Qualifications:

• Minimum of 8 years with BS/BA; Minimum of 6 years with MS/MA; Minimum of 3 years with PhD, 12 years of experience in lieu of degree
• Ability to Obtain Public Trust Clearance
• Must be a U.S Citizen
• Experience in leveraging AI-enabled testing tools
•  Familiarity with Selenium AI/ML Layer Plugins uses such as:
  • Self-Healing Tests for automatically identifying and updating broken element locators (e.g., XPath/CSS changes) using visual recognition, DOM similarity, or historical test data.
  • Dynamic Element Identification to recognize UI elements even if their properties (ID, class) have changed.
  • Visual Testing to compare baseline screenshots using AI-driven image recognition to detect visual regressions.
  • Smart Test Generation to analyze user flows, code changes, or logs to suggest or auto-generate new test cases.
  • Impact Analysis to predict which tests need to be rerun based on code or UI changes, reducing test cycles

Desired Qualifications:

• Strong foundation in
  • Software testing methodologies
  • Test automation frameworks
  • Defect tracking processes
• Proficiency with AI-enhanced platforms such as AI-enabled Selenium, which uses machine learning for adaptive test execution and element recognition
• AI-enabled Redwood, which supports self-healing test automation and intelligent error prediction
• Requires the ability to design and execute comprehensive test cases for functional, regression, and performance testing across web and enterprise applications.