About the role
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.
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