Why This Role Stands Out
Advance your career with an impactful role in AI-driven test automation, where you'll leverage cutting-edge GenAI tools to enhance software quality and delivery speed. This hybrid position is perfect for a skilled Quality Engineer eager to develop scalable automation solutions and contribute to innovative projects within a reputable organization. Join a dynamic team and seize this opportunity to grow your expertise in a forward-thinking environment.
Quick Overview
Job Description
Quality Engineer AI & Test Automation
Atlanta, GA (Hybrid)
Contract
Job Requirements
Quality Engineer AI & Test Automation
Role SummaryThe AI Automation Quality Engineer is responsible for developing intelligent and scalable test automation solutions using AI/GenAI, modern automation frameworks, and engineering practices to improve software quality, test coverage, and delivery speed.
This is a hands-on Quality Engineering and automation development role, not a primarily manual QA/testing position.
Key Responsibilities
Develop and maintain automated testing frameworks for UI, API, integration, regression, and end-to-end testing. Build AI-assisted test automation using GenAI tools to generate test cases, test data, automation scripts, and validation scenarios. Use AI to identify test coverage gaps, regression risks, defects, and potential failure scenarios. Automate API testing for REST/SOAP services and validate integrations across enterprise applications. Develop automated regression suites and integrate them into CI/CD pipelines.
Use AI to accelerate test-script generation, test maintenance, defect analysis, root-cause analysis, and test documentation. Develop and manage test data required for automated testing. Provide automated quality metrics and test results to support release-readiness decisions.
Pega Testing ExperienceExperience with Pega application testing is highly preferred, including:Pega case-management and workflow testing
Pega Constellation UICase Types, Stages, Assignments, SLAs and business rules
Experience or working knowledge of:
AI-assisted test-case generation
AI-assisted automation-code generation with github copilot
Automated test-data generation
AI-assisted identification of test-coverage gaps
AI-assisted defect/root-cause analysis
Using GenAI development tools to improve QE productivityTesting
AI/GenAI-enabled application capabilities
Understanding the challenges of validating non-deterministic
AI-generated outputs
Must-Have Technical Skills
Reusable automation components
Preferred Domain Experience
Pega-based enterprise applications
Healthcare dental insurance claims clinical enrollment provider or contactmcenter applications
Java Spring Boot APIs and microservicesLarge scale enterprise modernization programs
Candidate Expectations
Candidates whose recent experience is predominantly manual QA testing without significant hands-on automation development should not be submitted
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