Associate AI QA Engineer, Anaplan

• 3+ years of QA or test engineering experience, preferably with AI/ML systems
• Strong understanding of GenAI technologies including LLMs, prompt engineering, and AI application patterns
• Experience with test automation frameworks and scripting (Python, JavaScript, Selenium, Pytest)
• Knowledge of software testing methodologies (functional, integration, regression, performance, security testing)
• Ability to design test cases and evaluation criteria for non-deterministic systems
• Strong analytical and problem-solving skills with attention to detail
• Experience with API testing tools (Postman, REST Assured) and backend testing
• Familiarity with CI/CD pipelines and automated testing integration
• Excellent communication skills for documenting issues and collaboration
• Familiarity with LLM evaluation frameworks (LangSmith, PromptFoo, Ragas)

Desirable

• We're pioneering a new role focused exclusively on quality assurance for GenAI systems
• As our AI QA Engineer, you'll develop testing strategies, evaluation frameworks, and quality metrics specifically designed for LLM-powered applications
• This role requires a unique blend of QA expertise, understanding of GenAI behaviour, and automation skills to ensure our AI features are reliable, accurate, and trustworthy
• Design and implement comprehensive testing strategies for GenAI features, including conversational AI, agentic systems, and LLM-powered workflows
• Develop automated test suites for prompt testing, including regression tests that detect unintended changes in model behaviour
• Create evaluation frameworks to measure GenAI quality across multiple dimensions (accuracy, relevance, safety, consistency, latency)
• Build and maintain test datasets and golden examples that represent diverse user scenarios and edge cases
• Implement monitoring and alerting systems to detect quality degradation in production GenAI features
• Perform adversarial testing to identify potential failures, hallucinations, biases, or security vulnerabilities in AI systems
• Collaborate with engineers to define acceptance criteria and quality gates for AI feature releases
• Develop tools and frameworks that make it easy for engineers to test their GenAI implementations
• Conduct user acceptance testing and gather feedback on AI feature performance from internal users
• Document testing procedures, known issues, and quality metrics in clear, accessible formats
• Partner with Product and Design teams to ensure AI features meet user experience standards
• Stay current with GenAI testing methodologies, tools, and industry best practices
• Define QA practices for GenAI applications
• Work on cutting-edge AI technologies and help ensure they're reliable and trustworthy
• Shape quality standards that will impact millions of enterprise users
• Collaborate closely with engineers, data scientists, and product teams
• Grow expertise in a highly specialized and increasingly important domain
• Influence the entire AI product development lifecycle from design to release
• Join a team that values quality as a first-class concern, not an afterthought