Sr Manager, Applied Field Engineering - AI/ML

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. At Snowflake, we empower both enterprises and individuals to reach their full potential. Our culture prioritizes impact, innovation, and collaboration, making Snowflake the ideal place to build ambitious projects, execute quickly, and advance technology — and your career — to the next level. The Role We are seeking a Senior Manager, Applied Field Engineering — AI/ML Product Specialists to lead a high-performing team of AI/ML specialists at the intersection of product, field, and customer success. In this hands-on leadership role, you will manage a team of Applied Field Engineers who are deep practitioners in Snowflake's AI/ML product portfolio — including Cortex AI, ML modeling, and agentic workflows. You will drive product adoption and customer outcomes, ensuring customers move beyond initial activation to unlock the full depth of Snowflake's AI/ML capabilities. Critically, you will serve as a strategic bridge between the field and Snowflake's product organization — translating customer experience into structured product insight that directly shapes roadmap priorities. You will work closely with Product Management, Engineering, and Sales leadership to ensure Snowflake builds the right things and customers realize their full potential. Responsibilities & Focus Areas Product Adoption & Customer Outcomes: - Drive team performance toward meaningful product adoption — ensuring customers successfully build and scale AI/ML workloads on Snowflake and realize measurable business outcomes - Coach AFEs to lead with product depth, helping customers understand how Snowflake's AI/ML capabilities map to their use cases and data strategy - Review customer architectures with a product lens, guiding teams toward patterns that maximize long-term platform value and minimize technical debt - Actively engage in strategic customer conversations as a player/coach, modeling how to position Snowflake's AI/ML products against customer requirements and competitive alternatives Product Partnership & Roadmap Influence: - Own the field-to-product feedback loop for AI/ML: systematically gather, synthesize, and prioritize customer insights, product gaps, and adoption blockers from your team - Maintain direct relationships with AI/ML Product Management and Engineering counterparts — bring structured field signal into roadmap discussions and represent customer needs in product planning - Partner with Product Marketing to ensure field-facing materials accurately reflect current product capabilities, and flag gaps where messaging and product reality diverge - Participate in product beta programs, early access initiatives, and design partnerships — positioning your team and strategic customers as input sources for new AI/ML features - Partner with Sales leadership to align technical resources to pipeline and key account priorities where product depth is the differentiating factor Team Leadership & Development: - Recruit, onboard, and develop a team of Applied Field Engineers with exceptional AI/ML product depth — the bar is practitioners who have built with these technologies, not just presented them - Build a team culture where AFEs are recognized as product experts and trusted advisors, equally comfortable in a product roadmap discussion as in a customer architecture review - Conduct regular 1:1s, provide ongoing feedback, and invest actively in each AFE's technical and product knowledge development - Run internal enablement to keep the team current on Snowflake's evolving AI/ML product surface, including new Cortex capabilities, agent frameworks, and ML platform features On day one we will expect you to have: - 8+ years of experience in technical field roles (pre-sales, solutions engineering, product specialist, or technical consulting) with increasing scope and impact - 2+ years of people management experience leading technical specialist or product specialist teams - Deep product intuition: demonstrated experience working closely with product management — influencing roadmaps, contributing structured customer feedback, and translating field experience into product requirements - Hands-on AI/ML product expertise: practical depth in at least two of the following — Large Language Models / GenAI, ML model development and deployment, MLOps, Snowflake Cortex, or cloud-native AI/ML platforms - Customer outcome orientation: ability to drive product adoption and measurable customer value, not just initial activation or deal closure - Executive presence: confident engaging VP and Director-level stakeholders on both technical product capabilities and strategic business outcomes - University degree in computer science, engineering, mathematics, or a related field (or equivalent experience) About Our Team Our Applied Field Engineering team consists of deeply technical specialists who combine product expertise with customer empathy. We are passionate about ensuring Snowflake's AI/ML capabilities reach their full potential in production — and that what we learn in the field makes Snowflake's products better. Why Snowflake 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.