Validate AIgenerated responses against business requirements and acceptance criteria
Design and execute AI testing strategies prompt scenarios edge cases and adversarial tests
Evaluate NLP and LLM outputs for accuracy relevance consistency completeness and reliability
Measure response quality using defined evaluation metrics and benchmarks
Analyse data quality and identify issues impacting AI performance
Monitor model performance and user experience providing insights for continuous improvement
Develop and maintain benchmark datasets for validation and regression testing
Create and automate test scripts to improve testing efficiency and coverage
Conduct functional regression performance and usability testing for AI applications
Identify hallucinations bias toxicity and other AI risks
Support Responsible AI assessments including fairness transparency explainability and compliance reviews
Collaborate with AI engineers data scientists product teams and business stakeholders to improve model quality
Required Skills
Understanding of Generative AI NLP Machine Learning and Large Language Models LLMs
Experience in AI testing validation or quality assurance
Knowledge of prompt engineering test design and model evaluation techniques
Proficiency in Python or other scripting languages for test automation
Strong analytical and data evaluation skills
Experience with SQL Excel Power BI or similar reporting tools
Familiarity with AI quality metrics benchmarking and Responsible AI principles
Mandatory Skills : AI/Generative AI
Valuable to Have Skills : Functional/System Testing, Performance Testing -Chaos Engineering- Tools (Chaos Monkey,Gremlin), Selenium-Java -Testing, Test Design and Execution -Testing, User Acceptance Testing