Define and implement comprehensive quality assurance strategies and test plans for our AI agents and LLM-powered applications, ensuring exceptional product reliability and performance
Designing and developing automation frameworks: creating robust, scalable, and maintainable automated test frameworks from scratch or enhancing existing ones. You’ll need proficiency in at least one language like Typsecript, Python
Collaborate closely with product managers, machine learning engineers, and data scientists to understand complex AI features and model behaviors, translating them into effective test cases and validation criteria
Drive the continuous improvement of our testing processes and infrastructure, integrating automated checks within our CI/CD pipelines to ensure rapid, high-quality releases
Identify, document, and track software defects and inconsistencies, performing root cause analysis to provide actionable feedback to development teams
Monitor production systems and AI model performance, proactively identifying potential issues and contributing to post-release quality validation
Champion quality best practices across engineering teams, fostering a culture of ownership and continuous improvement in delivering world-class AI solutions
Designing, managing, and maintaining test data strategies and mock services to ensure stable, isolated, and repeatable test execution
Experience designing, developing, or integrating agentic AI systems, AI skills, and the Model Context Protocol (MCP)
Manage the full defect lifecycle by analyzing customer feedback and debugging logs to identify, prioritize, and track software bugs, collaborating closely with development teams to ensure timely resolution