AI Test Engineer

Job Summary

Education: B.E. / B.Tech / M.C.A or Equivalent. Job Location: DLF Phase III, Gurugram. Experience: 3 to 6 years. No. of Resources Required: 4. Job Reference Code: AITJ/0026.

Responsibilities

• Experience in testing AI/ML based applications, Generative AI platforms and Large Language Model (LLM) powered solutions.
• Strong understanding of AI testing methodologies including model validation, accuracy testing, fairness testing, explainability testing and hallucination detection.
• Hands-on experience in validating AI-generated responses, recommendations, predictions and decision-making systems.
• Experience in testing Generative AI applications using OpenAI, Gemini, Claude, Llama or similar AI models.
• Knowledge of Prompt Engineering, Prompt Validation and Prompt Optimization techniques.
• Experience in testing AI-powered chatbots, virtual assistants, conversational AI systems and intelligent automation solutions.
• Ability to create comprehensive AI testing strategies, test plans, test cases and test execution reports.
• Experience in Functional Testing, Integration Testing, Regression Testing and End-to-End System Testing of AI-enabled applications.
• Experience in API Testing using tools such as Postman, Swagger, REST Assured or equivalent technologies.
• Knowledge of Retrieval-Augmented Generation (RAG) architectures and validation of AI search and knowledge retrieval systems.
• Ability to evaluate AI model performance, response consistency, output relevance and business rule compliance.
• Experience in identifying model bias, fairness issues, security vulnerabilities and responsible AI concerns.
• Knowledge of AI data validation, training dataset quality assessment and data integrity testing.
• Experience in validating AI workflows across Web, Mobile, Desktop and Enterprise platforms.
• Strong understanding of Software Testing Life Cycle (STLC), Software Development Life Cycle (SDLC) and Agile methodologies.
• Hands-on experience with defect management tools such as JIRA, Azure DevOps or equivalent platforms.
• Experience in designing and implementing automation frameworks using Python, Selenium, Playwright or similar technologies.
• Ability to perform risk assessment and quality analysis for AI-driven business-critical applications.
• Experience working with cloud platforms such as AWS, Microsoft Azure or Google Cloud Platform will be an added advantage.
• Knowledge of Machine Learning concepts including classification, regression, clustering, recommendation systems and predictive analytics.
• Experience in testing AI/ML pipelines, model deployment workflows and production monitoring processes.
• Strong analytical, troubleshooting and problem-solving skills with a quality-first mindset.
• Excellent communication skills and ability to collaborate with Product Managers, Data Scientists, AI Engineers and Business Stakeholders.
• Ability to work independently and deliver high-quality testing solutions aligned with ELAARSONs Quality Engineering and AI Assurance practices.

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