Senior Manager, Applied Field Engineering - AI/ML Product Specialist
About the role
We are seeking a Manager, Applied Field Engineering - AI/ML Product Specialists to lead a high-performing team of Applied Field Engineers within the Applied Field Engineering organization. In this hands-on leadership role, you will manage a team of Applied Field Engineers who specialize in Generative AI, Machine Learning, and Advanced Analytics. You will be responsible for coaching your team through technical sales engagements, driving execution excellence, and ensuring customers successfully activate and consume Snowflake's AI/ML capabilities.
Responsibilities & Focus Areas
Drive team performance toward Consumption Activation — ensuring customers successfully move workloads into production and realize contracted credit value
Coach AFEs on technical sales engagement best practices, helping them identify and prioritize high-impact opportunities
Review and provide hands-on guidance on customer architectures to prevent technical debt and ensure scalability
Actively participate in customer engagements as a player/coach, modeling excellence in architectural discussions and executive-level conversations
Aggregate and communicate field insights to senior leadership; surface recurring product gaps and customer blockers to inform roadmap discussions
Partner with Sales leadership to ensure technical resources are aligned to regional pipeline and key account priorities
Participate in Communities of Practice and support knowledge-sharing initiatives across the team
Recruit, onboard, and develop a team of Applied Field Engineers, with a focus on technical growth and performance management
Build a culture of Technical Sales excellence where AFEs serve as trusted advisors to customers throughout the sales and post-sales lifecycle
Conduct regular 1:1s, provide ongoing feedback, and support career development for direct reports
Requirements
8+ years of industry experience in a pre-sales, technical sales, or technical consulting capacity
2+ years of people management experience, preferably leading technical overlay or specialist teams
Experience with Consumption-based models: Ability to drive not just deal closures, but actual activation and usage of software services
Technical credibility: Hands-on depth in at least one of the following: GenAI/LLMs, Machine Learning, Data Engineering, or Cloud Data Architecture
Communication skills: Ability to engage confidently with VP and Director-level stakeholders and translate technical value into business outcomes
Qualifications
University degree in computer science, engineering, mathematics, or related fields (or equivalent experience)