#23016-SDET - AI ML Validation Engineer

Chatbot & RAG Testing • LLM/Prompt Evaluation • Python Validation

AI Solution Testing: Validates AI-powered solutions including chatbots and generative AI features for accuracy, reliability, and edge cases

RAG Validation: Tests Retrieval-Augmented Generation pipelines for retrieval relevance, grounding, and hallucination handling

Agentic AI: Builds and tests agentic solutions such as MCP and prompting

Data Quality • AI Eval Metrics • Responsible AI

Test Data Management: Curates and versions golden/evaluation datasets and validates data pipelines for integrity, completeness, and drift across training and inference

AI Evaluation: Hands-on with evaluation frameworks and metrics such as RAGAS, DeepEval, and LLM-as-judge, covering groundedness, relevance, and precision/recall

Responsible AI & Privacy: Bias and fairness checks, safety/guardrail, and PII/data-leakage validation

Python • Pytest

Core Languages: Proficient in Python for automation

Test Frameworks: Hands-on with Pytest, or equivalent

Framework Design: Build, scale, and maintain automation frameworks end-to-end

UI Automation • REST/GraphQL APIs • Contract Testing

UI Automation: End-to-end browser testing across modern web applications. Well versed with BDD frameworks like Cucumber/SpecFlow