Job Summary

We are seeking a QA Engineer – AI with 3–7 years of experience to validate AI-powered applications, automation workflows, and intelligent systems. The ideal candidate should have strong expertise in manual and automation testing, API testing, and experience validating Generative AI/LLM-based applications. You will work closely with developers, AI engineers, and product teams to ensure the quality, reliability, and performance of AI solutions.

Key Responsibilities

Design, develop, and execute comprehensive test plans, test cases, and test scenarios for AI-enabled applications.
Perform functional, regression, integration, system, and end-to-end testing.
Validate AI/LLM outputs for accuracy, consistency, hallucinations, bias, and edge cases.
Develop and maintain automation frameworks for web and API testing.
Perform REST API testing using Postman, Rest Assured, or similar tools.
Create and execute test data strategies for AI model validation.
Work with developers to identify, reproduce, and resolve defects.
Validate prompt engineering scenarios and AI workflow integrations.
Execute performance and reliability testing for AI-powered applications.
Participate in Agile ceremonies, sprint planning, and defect triage meetings.
Maintain test documentation, defect reports, and quality metrics using JIRA or Azure DevOps.

Mandatory Skills

3–7 years of experience in Software Testing/QA.
Strong experience in Manual Testing and Automation Testing.
Hands-on experience with Selenium WebDriver .
Programming knowledge in Java or Python .
Experience with TestNG/JUnit and automation frameworks.
Strong understanding of API Testing using Postman and/or Rest Assured.
Knowledge of SQL and database validation.
Hands-on experience with Git and version control.
Experience working in Agile/Scrum environments.
Exposure to Generative AI , LLMs (ChatGPT, Gemini, Claude, etc.) , prompt testing, or AI application validation.
Experience with defect tracking tools such as JIRA .

Preferred Skills

Experience testing applications built on OpenAI, Azure OpenAI, Google Vertex AI, AWS Bedrock , or similar AI platforms.
Knowledge of Python scripting for test automation.
Experience with Playwright or Cypress.
Exposure to CI/CD tools such as Jenkins, GitHub Actions, or Azure DevOps.
Understanding of Docker and basic Kubernetes concepts.
Experience with performance testing tools such as JMeter.
Familiarity with AI evaluation metrics, prompt engineering, Retrieval-Augmented Generation (RAG), and vector databases is an added advantage.