QA Engineer with AI

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.

• 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.
  

• 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.
  

• 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.
  

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
  

• Strong analytical and problem-solving abilities.
  

• Excellent communication and collaboration skills.
  

• Ability to work independently and in cross-functional teams.
  

• Attention to detail with a quality-first mindset.
  

• Eagerness to learn emerging AI technologies and testing methodologies.