AI Quality Engineer Location:- Hyderabad Work Mode:- WFO (5 days a week) Role Type:- Contractual (3 months and extension would depend on project requirement and performance) Key Responsibilities • Test and validate AI-generated insights, recommendations, and decision-making workflows. • Evaluate LLM and RAG systems for accuracy, relevance, consistency, factuality, and hallucinations. • Validate retrieval quality, context relevance, grounding, and response quality in RAG systems. • Test AI agents and autonomous workflows across functional, negative, and edge-case scenarios. • Define AI evaluation criteria, test datasets, quality metrics, and validation processes. • Perform regression testing for models, prompts, RAG configurations, and AI workflows. • Collaborate with AI/ML engineers to identify issues and improve AI system quality. Requirements Required Skills • Strong understanding of AI/ML and Generative AI testing. • Hands-on experience testing LLM and RAG-based applications. • Knowledge of LLM evaluation, hallucination detection, relevance, and response quality. • Understanding of AI agents and recommendation systems. • Strong analytical and problem-solving skills. Good to Have • Experience with PyTest and automated testing frameworks. • Experience building automated AI evaluation and regression frameworks. • Familiarity with tools such as RAGAS, DeepEval, LangSmith, or equivalent. • Experience with CI/CD-based test automation, performance testing, or AI guardrails. • Familiarity with cloud platforms (AWS/Azure/GCP) and observability tools. Success Metrics • High accuracy, relevance, and reliability of AI outputs. • Strong evaluation coverage across critical AI workflows. • Early detection and reduction of hallucinations and AI regressions. • Reduced production AI quality issues. • Increased confidence and trust in AI-generated insights and recommendations.