Quality Engineer, Ai Native
Salary: $120,000
Must Haves:
- 2+ years of hands-on test automation experience
- Professional experience using AI-assisted tools (Copilot, Claude, ChatGPT) for test generation and analysis
- Strong Playwright + TypeScript experience for UI / E2E testing
- Experience writing code-based API tests (TypeScript or C# with xUnit/NUnit)
- Working knowledge of C# / .NET applications (ability to read and understand code)
- Experience testing REST APIs (contracts, schemas, business logic, error handling)
- Experience validating data using SQL Server or Azure SQL
- Hands-on experience integrating automated tests into Azure DevOps CI/CD pipelines
- Strong judgment reviewing and validating AI-generated tests
Pluses:
- Experience in agentic or AI-native engineering environments
- Exposure to React and Angular front-end applications
- Experience with integration testing across distributed services
- Prior work partnering with offshore QE teams
- Background in highly regulated or workflow-heavy domains (fintech, legal tech, healthcare)
- Strong ownership mindset with emphasis on test reliability and quality gates
Job Description:
Insight Global is seeking a Quality Engineer, AI Native for a leading technology-driven solutions organization operating at the intersection of legal, healthcare, and financial services. This engineer will play a critical role in owning automated quality coverage across UI, API, and integration layers in an AI-accelerated development environment. The ideal candidate is highly technical, automation-first, and confident applying strong quality judgment in environments where AI agents contribute to code at scale. This is an excellent opportunity for a QE who wants to shape what “quality” means in a modern, AI-native delivery model while working on impactful, mission-driven products.
Day-to-Day:
- Design, build, and maintain automated UI and E2E tests using Playwright/TypeScript
- Develop and maintain automated API tests for ASP.NET Core services
- Create integration tests validating service-to-service data flows
- Design reliable test data strategies for parallel execution
- Leverage AI tools to accelerate test creation while critically validating outputs
- Serve as the quality gatekeeper in an AI-driven development model
- Integrate and maintain automated test execution in Azure DevOps pipelines
- Log, track, and partner on defect resolution in Jira
- Participate in sprint planning, risk assessment, and acceptance criteria definition
- Collaborate with onshore and offshore QEs to maintain shared quality standards