QA Engineer / Senior QA Engineer – GenAI Testing

Job Description – QA Engineer (Python + GenAI

Testing + UiPath)

Role

QA Engineer / Senior QA Engineer – GenAI Testing

Experience

4-8 Years

Job Summary

We are looking for a highly skilled QA Engineer with strong experience in Python, UI

Automation, UiPath, API Testing, and GenAI Application Testing. The candidate will

be responsible for validating AI-powered applications, Agentic AI workflows, RAG

solutions, LLM-based chatbots, and enterprise automation solutions.

The ideal candidate should possess a strong testing mindset and be capable of

validating both traditional software applications and AI-driven systems.

Mandatory Skills

Python

 Test Automation Development

 API Automation using Python

 Data Validation Scripts

 JSON Processing

UI Automation

UiPath

 UiPath Studio

 UiPath Test Suite

 Workflow Validation

 UiPath Orchestrator

 End-to-End Automation Testing

API Testing

 Postman

 REST APIs

 Swagger

 JSON/XML Validation

Database Testing

 SQL

 Data Reconciliation

 Backend Validation

Defect Management

 Jira

Agile

 Scrum

 Sprint Testing

 Test Planning & Estimation

GenAI Testing Experience (Good to have)

Candidate should have hands-on experience testing one or more of:

GenAI Validation

 Prompt Testing

 Prompt Engineering Validation

 Output Verification

 Hallucination Detection

 Grounding Validation

 Toxicity Testing

 Bias Testing

 Response Quality Evaluation

Agentic AI Testing

 Multi-Agent Workflows

 Agent Decision Validation

 Human-in-the-Loop Testing

Enterprise AI Use Cases

Experience testing:

 AI Chatbots

 Virtual Assistants

 Document Processing Solutions

 Document Q&A Systems

Key Responsibilities

 Create Test Strategy for GenAI applications.

 Design test cases for LLM and RAG systems.

 Build Python-based automation frameworks.

 Validate AI-generated outputs.

 Perform UiPath workflow testing.

 Execute UI, API, Database, and Integration testing.

 Track defects and support root cause analysis.

 Automate regression test suites.

 Validate AI response correctness and consistency.

 Perform performance and reliability testing for AI applications.

 Work closely with Architects, Developers, Product Owners, and Business teams.