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Quality Engineer (Automation, AI experience)

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Onsite

Quality Engineer (Automation, AI experience)

Core Alliance Group Inc.

Quality Engineer (Automation, AI experience)

Skills

JavaTesting & QASpring BootAIGitHub

2 months ago

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Important information


Contract type:

Freelance / Contract, Temporary

Location:

Atlanta, GA, USA

Work mode:

Onsite

Published on:

12 September 2026

What they need


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

Work Location: In person

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