Principal AI Software Engineer - Snowflake Intelligence
Snowflake · US-CA-Menlo Park
About this role
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset - who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. ABOUT THE ROLE The Cortex Apps team is defining the future of AI for enterprise data. Our mission is to transform how the world’s largest enterprises interact with their data through flagship products like Snowflake Intelligence. As a Principal AI Engineer, you will be a technical North Star for our AI initiatives. You won't just execute on a roadmap; you will help define it. You will tackle the most complex, "frontier" problems in agentic reasoning, NL-to-SQL, and enterprise-scale RAG, ensuring our AI products are not only innovative but fundamentally reliable and scalable for the Fortune 500. WHAT YOU WILL DO IN THIS ROLE: - Technical Strategy & Architecture: Define the long-term technical vision for Snowflake Intelligence. Lead the architectural design of multi-agent systems, complex tool-use frameworks, and self-correcting NL-to-SQL engines. - Drive Industry-Leading Reliability: Move beyond simple evals to build world-class, automated "hill-climbing" infrastructure. You will establish the methodology for how Snowflake measures and guarantees LLM performance across diverse customer schemas. - Cross-Functional Influence: Partner with Product and Engineering leadership to align AI capabilities with business goals. You will bridge the gap between Research (modeling) and Pro
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