Automation Testing with AIML

Technical Skills – Must have    Lead the design and development of AI-driven test automation frameworks and solutions.  Collaborate with stakeholders (e.g., product managers, developers, data scientists) to understand testing requirements and identify areas where AI automation can be effectively implemented.  Develop and implement test automation strategies for AI-based systems, encompassing various aspects like data generation, model testing, and performance evaluation.  Evaluate and select appropriate tools and technologies for AI test automation, including AI frameworks, testing tools, and automation platforms.  Define and implement best practices for AI test automation, covering areas like code standards, test case design, test data management, and ethical considerations.  Lead and mentor a team of test automation engineers in designing, developing, and executing AI test automation solutions.  Collaborate with development teams to ensure the testability of AI models and systems, providing guidance and feedback throughout the development lifecycle.  Analyze test results and identify areas for improvement in the AI automation process, continuously optimizing testing effectiveness and efficiency.  Stay up-to-date with the latest advancements and trends in AI and automation technologies, actively adapting and implementing new knowledge to enhance testing capabilities.  Knowledge in Generative AI and Conversational AI for implementation in test automation strategies is highly desirable.  Proficiency in programming languages commonly used in AI, such as Python, Java, or R.  Knowledge on AI frameworks and libraries, such as TensorFlow, PyTorch, or scikit-learn.  Familiarity with testing methodologies and practices, including Agile and DevOps.  Working experience on Python/Java and Selenium also knowledge in prompt engineering.