Software Quality Engineer

You will be joining the Red Hat Quality Engineering team in Pune with a focus on Generative AI applications. As a Quality Engineer, your responsibilities will include: - Designing and executing test cases to validate the functionality, performance, and reliability of Generative AI solutions. - Performing testing on data validation scenarios, data ingestion, pipelines, and transformation processes (ETL). - Testing and automating API functionalities using tools like Postman or Rest Assured. - Developing and maintaining automated test scripts for performance, functional, integration, and regression testing. - Collaborating with stakeholders to identify testing requirements, set priorities, and resolve issues in a timely manner. - Identifying and documenting defects, issues, and risks related to Generative AI implementations. - Driving continuous improvement and establishing best practices for testing methodologies and AI quality standards. - Staying updated with the latest advancements in AI testing, tools, and frameworks, including bias detection and fairness evaluations. - Providing detailed reports and presenting testing results to leadership, offering clear, business-focused insights. - Influencing team members to follow testing standards and procedures for AI systems. Qualifications required for this role: - Bachelor's degree in information technology (IT) or computer science with 2+ years of related experience. - Experience in API testing using Postman/Rest Assured. - Proficiency in performance testing and automation tools. - Familiarity with automated testing and continuous integration tools. - Experience setting testing standards and influencing quality processes. - Strong analytical and problem-solving skills, with attention to detail. - Excellent communication and presentation skills, capable of translating complex concepts into actionable insights for stakeholders. - Experience in Agile development environments. - Proven experience in Python scripting for Generative AI applications. - Familiarity with testing data pipelines, data validation, and ETL processes. - Intermediate decision-making skills on day-to-day development. - Intermediate written and verbal communication skills in English. Plus to have: - Experience in ethical AI testing, including bias detection and fairness evaluations. - Familiarity with cloud platforms (AWS, Google Cloud, Azure) for AI/ML model deployment. - Understanding of data privacy and security best practices for AI systems. - Knowledge of statistics and DevOps processes is a plus.,