QA Engineer

Key Responsibilities: Quality Assurance & Testing Design, develop, and execute test plans, test cases, and test scripts for AI-powered applications and services. Perform functional, integration, system, regression, and user acceptance testing (UAT) support. Validate end-to-end workflows across AI applications, APIs, and integrated systems. Identify, document, track, and verify resolution of defects and issues. This role is for one of our project requirements Model Upgrade Validation Support testing and validation activities during AI model upgrades. Conduct model output comparisons and regression testing to assess the impact of model changes Validate model performance against predefined quality metrics such as accuracy, relevance, consistency, and completeness. Technology Upgrade & Release Support Support testing for AI models during infrastructure, platform, security, and technology upgrades. Validate system stability following upgrades to application frameworks, libraries, APIs, and supporting technologies. Participate in release readiness reviews, production deployment validation, and post-release verification. Ensure appropriate test evidence and documentation are maintained for audit and governance purposes Operational Support Support production incident investigations related to model or technology changes. Assist with root cause analysis and validation of fixes. Monitor service quality trends and provide recommendations for quality improvements. Work closely with Group Operations and Technology teams to ensure service reliability and business continuity. Requirements: Education & Experience Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline. 6-9 years of experience in software quality assurance, testing, or quality engineering. Experience supporting enterprise applications, AI/ML solutions, or digital platforms is preferred. Experience in banking, financial services, or operations environments is advantageous. Technical Skills Strong understanding of software testing methodologies and SDLC/STLC processes. Experience with API testing tools such as Postman, Swagger, or equivalent. Familiarity with SQL and data validation techniques. Knowledge of test automation frameworks and scripting languages (e.g., Python, Selenium, Playwright). Understanding of CI/CD pipelines and DevOps practices. Familiarity with AI/ML or GenAI concepts, model testing, and prompt validation. Exposure to monitoring, logging, and observability tools is a plus.