Key Responsibilities:

• Develop and Execute Tests: Create and run manual and automated test cases and test scripts for AI systems and traditional software applications.
• Defect Management: Identify, document, and track software defects and issues using bug tracking systems (e.g., Jira).
• AI-Specific Testing: Assist in testing AI model accuracy, evaluating outputs for bias, and performing prompt testing for generative AI systems.
• Documentation and Reporting: Create and maintain comprehensive test documentation, including test plans, test cases, and test reports.
• Collaboration: Work closely with developers, product managers, and data scientists in an Agile environment to understand requirements and resolve quality issues.
• Exploratory Testing: Participate in exploratory testing sessions to discover issues and provide feedback on product usability from a user-oriented perspective.
• Continuous Improvement: Proactively contribute to the improvement of QA processes and learn new testing tools and technologies.

Skills & Qualifications:

• Education: A Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field is beneficial but not always mandatory if strong skills are demonstrated.
• Foundational Knowledge: Basic understanding of software testing methodologies (e.g., Agile, Scrum) and the software development lifecycle (SDLC).
• Analytical Skills: Strong analytical thinking, attention to detail, and problem-solving abilities are crucial for identifying subtle issues.
• Programming Basics (Preferred): Familiarity with programming concepts or languages such as Python or Java is a plus, especially for learning test automation.
• Communication: Excellent written and verbal communication skills to clearly articulate issues and collaborate with team members.
• Interest in AI: A genuine interest in artificial intelligence, machine learning fundamentals, and related technologies.