Maggie Phillips

Fast Facts: Formal Job Title: AI - Native Quality Engineer Terms: Adding after req call! Pay Rate: Adding after req call! Converting Salary Range : $100K Hiring Manager : Trent Donelson & Ray Ritz Target Start Date : 7/1/26       Job Summary : The Quality Engineer, AI-Native is a core contributor on the quality engineering team, responsible for designing and owning automated test coverage across API, UI, and integration layers within Libra Solutions’ AI-native delivery model. This role requires hands-on automation expertise and the ability to operate effectively as the quality safeguard in an agentic engineering environment — where AI agents contribute to code and test generation at scale and engineers own the judgment, coverage depth, and quality standards that define what ships   This position reports to the Manager, Quality Engineering and can be based in any of our office locations in Denver, CO, Huntersville, NC, Rosemont, IL, or Las Vegas, NV. We welcome strong remote candidates, with occasional travel to Las Vegas as needed.   Responsibilities:  

• Design, implement, and maintain automated UI and end-to-end test suites using Playwright / TypeScript, covering critical user workflows across React and Angular front-end applications
• Write automated API tests against C# / ASP.NET Core REST endpoints using TypeScript HTTP client libraries or C# / xUnit / NUnit test projects; validating request contracts, response schemas, business logic, and error handling
• Build and maintain integration tests that validate service-to-service interactions and data flows across the application stack, including SQL Server / Azure SQL data validation
• Contribute to test data strategy for the squad’s automated suites: design repeatable, isolated data setup and teardown that enables reliable parallel test execution
• Use AI-assisted tools (GitHub Copilot, Claude) with structured prompts to accelerate test scaffolding and test generation across API, UI, and integration layers
• Critically evaluate all AI-generated tests before committing — review for coverage completeness, assertion quality, and absence of false confidence
• Work within Libra’s agentic engineering model: AI agents accelerate code generation at scale; QEs own the quality judgment that determines what ships
• Contribute to Azure DevOps CI/CD pipelines, ensuring automated suites run as mandatory quality gates on every build with actionable pass/fail signal
• Identify, document, and track bugs/defects in Jira with clear reproduction steps and test evidence; partner with engineers to drive timely resolution
• Participate in sprint ceremonies and contribute to test planning, risk assessment, and acceptance criteria definition alongside the Technical Product Owner
• Partner with offshore QE engineers on the squad to scope test cases clearly, provide review feedback, and maintain shared quality standards

  Requirements / Ideal Profile :  

• Bachelor’s degree in Computer Science, Information Technology, or related field, or equivalent professional experience
• 2+ years of hands-on test automation experience writing code-based test suites
• Proficiency in Playwright and TypeScript for UI and end-to-end test automation
• Experience writing automated API tests in code (TypeScript HTTP clients, C# / xUnit / NUnit, or equivalent), not just exploratory API testing with Postman
• Working knowledge of C# / .NET applications as the system under test; ability to read C# code to understand expected behavior
• Familiarity with SQL Server or Azure SQL for data validation within automated tests
• Experience integrating automated tests into Azure DevOps CI/CD pipelines as quality gates
• Hands-on experience with AI tools (GitHub Copilot, Claude, ChatGPT) for test scaffolding, test data generation, and defect analysis
• Understanding of the QE role in an agentic delivery model: able to adapt test strategy and coverage to environments where AI agents contribute significantly to code generation, with heightened focus on validation depth, assertion quality, and critical evaluation of AI-generated test output
• Creative problem-solving and troubleshooting skills
• Self-motivated, ownership-oriented, and technically precise; treats test reliability as a first-class concern

    Screening Questions : Adding after req call!