Senior Manager, Applied Field Engineering - AI/ML Product Specialist

Snowflake is a company that empowers enterprises and individuals to reach their full potential through innovative technology. The role involves leading a team of Applied Field Engineers specializing in AI/ML, driving technical sales engagements, and ensuring successful customer activation of Snowflake's capabilities.

Responsibilities:

• 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
• Education: University degree in computer science, engineering, mathematics, or related fields (or equivalent experience)