Posted:16 hours ago
Role Purpose
The purpose of this role is to develop multi-module test cases and set up test environments while preparing test evidence and validating system functionality.
Experience : 6-10 Years
Role Summary: We are seeking a GenAI Testing professional with experience in validating Large Language Models (LLMs), Agentic AI systems, RAG applications, and AI-powered business solutions. The candidate will drive quality assurance for GenAI implementations, ensuring accuracy, reliability, security, and business alignment of AI-generated outcomes.
Key Responsibilities
Design and execute test strategies for GenAI, RAG, Copilot, and Agentic AI applications.
Validate AI responses for accuracy, relevance, consistency, bias, toxicity, and hallucinations.
Develop AI-specific test scenarios, prompt libraries, and evaluation frameworks.
Create automated validation approaches for LLM outputs.
Perform prompt engineering and prompt optimization activities.
Test Retrieval-Augmented Generation (RAG) workflows and knowledge-grounding mechanisms.
Validate AI guardrails, compliance requirements, and security controls.
Collaborate with Product Owners, Business SMEs, Data Scientists, and AI Architects.
Define KPIs and quality metrics for AI solution evaluation.
Support GenAI adoption initiatives and recommend QA best practices.
Mandatory Skills
GenAI Testing Concepts
LLM Validation & Evaluation
Prompt Engineering
RAG Testing
Functional & Automation Testing
API Testing
Python
AI Model Evaluation Techniques
Jira / Azure DevOps
Agile Delivery Model
Good to Have
Azure OpenAI / OpenAI
LangChain / LangGraph
MCP (Model Context Protocol)
Agentic AI Platforms
GitHub Copilot
AI Security Testing
Python-based Automation Frameworks
Free courses, interview questions and practice for each skill.
Wipro
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