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.
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Perform functional, regression, integration, system, and end-to-end testing.
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Validate AI/LLM outputs for accuracy, consistency, hallucinations, bias, and edge cases.
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Develop and maintain automation frameworks for web and API testing.
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Perform REST API testing using Postman, Rest Assured, or similar tools.
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Create and execute test data strategies for AI model validation.
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Work with developers to identify, reproduce, and resolve defects.
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Validate prompt engineering scenarios and AI workflow integrations.
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Execute performance and reliability testing for AI-powered applications.
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Participate in Agile ceremonies, sprint planning, and defect triage meetings.
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Maintain test documentation, defect reports, and quality metrics using JIRA or Azure DevOps.
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3–7 years of experience in Software Testing/QA.
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Strong experience in Manual Testing and Automation Testing.
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Hands-on experience with Selenium WebDriver .
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Programming knowledge in Java or Python .
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Experience with TestNG/JUnit and automation frameworks.
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Strong understanding of API Testing using Postman and/or Rest Assured.
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Knowledge of SQL and database validation.
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Hands-on experience with Git and version control.
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Experience working in Agile/Scrum environments.
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Exposure to Generative AI , LLMs (ChatGPT, Gemini, Claude, etc.) , prompt testing, or AI application validation.
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Experience with defect tracking tools such as JIRA .
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Experience testing applications built on OpenAI, Azure OpenAI, Google Vertex AI, AWS Bedrock , or similar AI platforms.
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Knowledge of Python scripting for test automation.
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Experience with Playwright or Cypress.
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Exposure to CI/CD tools such as Jenkins, GitHub Actions, or Azure DevOps.
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Understanding of Docker and basic Kubernetes concepts.
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Experience with performance testing tools such as JMeter.
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Familiarity with AI evaluation metrics, prompt engineering, Retrieval-Augmented Generation (RAG), and vector databases is an added advantage.
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Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
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Strong analytical and problem-solving abilities.
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Excellent communication and collaboration skills.
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Ability to work independently and in cross-functional teams.
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Attention to detail with a quality-first mindset.
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Eagerness to learn emerging AI technologies and testing methodologies.
