AI QA Engineer

Required Skills & Experience:

• 5+ years of experience in QA / Quality Engineering.
• 2+ years testing AI systems including LLM apps, RAG pipelines, and agentic workflows.
• Python proficiency for automation, test harnesses, and evaluation development.
• Experience testing data/AI pipelines in Snowflake and at least one major cloud (AWS/Azure).
• Experience with distributed systems, API testing, and CI/CD.
• Strong communication and collaboration skills.

Job Description:

• We are seeking a Senior AI QA Test Engineer with deep expertise in AI/ML quality engineering and hands-on experience testing enterprise-grade Agentic GenAI systems.
• This role focuses on ensuring the performance, reliability, and safety of our AI ecosystem across Snowflake, AWS, and Azure.
• The engineer will design and implement quality assurance strategies for LLM, RAG, and agentic AI pipelines; develop automated test suites for agent workflows, LLM applications, APIs, and vector-search systems; and validate retrieval workflows, grounding, reasoning patterns, and hallucination reduction.
• The role also involves building robust evaluation pipelines with metrics and regression frameworks, implementing AI observability including telemetry and drift monitoring, integrating automated testing into CI/CD processes, and defining enterprise-level QA best practices for AI governance and system reliability.