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.

Required Skills
Robust 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.




Robust 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.
Solid 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.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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