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Snowflake is seeking a Principal AI Software Engineer to join the Cortex CoWork team, which is defining the future of AI for enterprise data. In this role, you will serve as a technical North Star for Snowflake's AI initiatives, tackling frontier problems in agentic reasoning, natural language-to-SQL translation, and enterprise-scale retrieval-augmented generation (RAG).
You will own technical strategy and architecture, defining the long-term vision for Snowflake Intelligence and leading the design of multi-agent systems, complex tool-use frameworks, and self-correcting NL-to-SQL engines. A core responsibility is establishing world-class, automated evaluation and "hill-climbing" infrastructure to measure and guarantee LLM performance across diverse customer schemas at scale.
You will partner closely with Product and Engineering leadership to align AI capabilities with business goals, bridging the gap between Research (modeling) and Production (infrastructure) to ensure cutting-edge LLM breakthroughs are viable at Snowflake's scale. You will design extensible "context engineering" patterns—including advanced function calling and semantic layer integration—that can be leveraged across Snowflake teams and external developers.
As a technical leader, you will mentor Staff and Senior engineers, lead cross-functional strike teams on high-stakes projects, and foster a culture of technical excellence and rapid experimentation. You will communicate complex technical trade-offs effectively to both executive leadership and individual contributors.
Required qualifications include 10+ years of software engineering experience with 3+ years specifically leading the deployment of LLM-based applications at massive scale. You should hold a Bachelor's, Master's, or PhD in Computer Science, AI, or a related field. Deep expertise in LLM orchestration, prompt optimization, semantic modeling, and building robust guardrails for non-deterministic systems is essential. You must have a proven track record designing complex systems that integrate AI with traditional data stacks (SQL, retrieval systems, semantic layers) and have previously held a Principal or equivalent high-level IC role or led the technical launch of a major AI product used by millions.
