Lead Software Engineer

Virtusa Corp

  • Alpharetta, GA
  • 14 days ago

    Highlights

    The 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. Build AI-assisted test automation using GenAI tools to generate test cases, test data, automation scripts, and validation scenarios.

    Numbers & Facts

    LocationAlpharetta, GA

    Description

    Quality Engineer - AI & Test Automation

    Role Summary

    The 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 Experience

    Experience with Pega application testing is highly preferred, including:

    Pega case-management and workflow testing

    Pega Constellation UI

    Case 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 productivity

    Testing 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 microservices

    Large 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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