AI Test Automation Developer

As an AI Test Automation Developer in Bangalore hybrid, your responsibilities will include developing AI-driven test agents to automate routine testing tasks such as test case generation, documentation, and scripting. You will be responsible for implementing automation frameworks for testing AI models and software components, as well as integrating test automation solutions into existing frameworks. Additionally, you will design and develop automated test scripts using open-source tools and frameworks, and identify, analyze, and document defects in AI models and software applications. Collaboration with developers and data scientists to ensure AI algorithms meet quality standards is a key aspect of your role. Monitoring and troubleshooting AI system performance to improve accuracy and efficiency, integrating security testing into the automation framework to identify vulnerabilities, and conducting penetration testing to assess security risks in AI-powered applications are also part of your responsibilities. Ensuring compliance with security standards and best practices for AI models and software, as well as staying updated on industry trends and advancements in AI testing methodologies and cybersecurity, are essential for success in this role. To qualify for this position, you should have a Bachelor's degree in computer science or equivalent, along with a minimum of 10 years of experience in QA test automation development. Proficiency in programming languages such as C#, Java, or Python is required. Hands-on experience with test automation tools like Selenium, TestNG, Junit, Playwright, or equivalent is necessary. Strong knowledge of AI/ML concepts, particularly LLMS and Gen AI testing frameworks and techniques, is essential. Experience working with CI/CD pipelines and tools like Jenkins, GitHub Actions, or Azure DevOps is preferred. Understanding security testing methodologies, including penetration testing and vulnerability assessments, is a key requirement. Experience with web applications, mobile apps, and cloud platforms (AWS, Azure, or Google Cloud) for AI model deployment and testing is beneficial. Strong experience with testing the reliability and accuracy of synchronous APIs by verifying request-response interactions and asynchronous APIs is also important. Deep knowledge of user story to test case translation with methods like Gherkin/Cucumber or equivalent is required. The ability to quickly grasp and distill highly complex user design issues into clean, understandable solutions is a must. You must be able to flourish in a fast-paced, iterative, deadline-driven environment. Strong communication and organizational skills are critical to success among a company of talented individuals.,