QA Engineer – AI & Application Testing
Company: Global KTech Inc.,
Location: Remote (Remote)
Salary: $55 - $60 an hour
Type: Full-time
Remote: Yes
Posted: 2026-10-13
About this role
Job Overview
We are seeking a highly motivated and detail-oriented QA Engineer specializing in AI and Application Testing to join our dynamic team. In this role, you will be responsible for ensuring the quality, functionality, and performance of cutting-edge AI-driven applications and software solutions. Your expertise will help drive the development of robust, reliable, and user-friendly products by designing comprehensive test plans, executing rigorous testing procedures, and collaborating closely with cross-functional teams. If you thrive in a fast-paced environment and are passionate about delivering exceptional software quality, this opportunity is perfect for you!
Duties
- Role Summary: Tests AI model outputs and application functionality. Validates data accuracy, business logic and system performance.Key Resposibilities:- Design and execute test plans covering AI model outputs, data correctness, and application functionality.- Create automated tests for APIs and UI where appropriate; maintain regression suites.- Validate business logic, edge cases, and non-functional requirements (performance, reliability).- Establish evaluation criteria for AI components (accuracy, hallucination checks, guardrail adherence).- Triage defects, document reproducible steps, and partner with engineers to resolve issues.- Contribute to release readiness, quality gates, and continuous improvement of testing practices.Required Qualifications:- 4+ years in QA/Test Engineering for web/services-based applications.- Experience with test automation tools (Selenium) and API testing (Postman or similar).- Strong understanding of test case design, defect lifecycle, and agile QA practices.- Familiarity with tracking tools (JIRA) and test documentation.- Ability to reason about data quality and validate outputs against requirements.Preferred Nice to have:- Experience testing ML/LLM systems: evaluation datasets, prompt regressions, safety checks.- Performance testing experience (loa...