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Snowflake is seeking a Senior Manager of Applied Field Engineering to lead a high-performing team of AI/ML specialists bridging product, field, and customer success. This hands-on leadership role manages Applied Field Engineers who are deep practitioners in Snowflake's AI/ML product portfolio, including Cortex AI, ML modeling, and agentic workflows.
Key responsibilities include driving product adoption and customer outcomes by coaching AFEs to lead with product depth, helping customers understand how Snowflake's AI/ML capabilities map to their use cases, and reviewing customer architectures with a product lens. You will serve as a strategic bridge between the field and Snowflake's product organization, translating customer experience into structured product insight that shapes roadmap priorities.
You will own the field-to-product feedback loop for AI/ML by systematically gathering, synthesizing, and prioritizing customer insights, product gaps, and adoption blockers. Maintain direct relationships with AI/ML Product Management and Engineering counterparts, bringing structured field signal into roadmap discussions and representing customer needs in product planning. Partner with Product Marketing to ensure field-facing materials accurately reflect product capabilities and flag messaging gaps.
Team leadership involves recruiting and developing Applied Field Engineers with exceptional AI/ML product depth—practitioners who have built with these technologies. Build a team culture where AFEs are recognized as product experts and trusted advisors, equally comfortable in product roadmap discussions as in customer architecture reviews. Conduct regular 1:1s, provide ongoing feedback, and invest actively in each team member's technical and product knowledge development.
Required qualifications: 8+ years in technical field roles (pre-sales, solutions engineering, product specialist, or technical consulting) with increasing scope; 2+ years leading technical specialist or product specialist teams; deep product intuition with demonstrated experience influencing roadmaps and translating field experience into product requirements; hands-on AI/ML product expertise in at least two areas (LLMs/GenAI, ML model development/deployment, MLOps, Snowflake Cortex, or cloud-native AI/ML platforms); customer outcome orientation; executive presence engaging VP and Director-level stakeholders; university degree in computer science, engineering, mathematics, or related field (or equivalent).
