Senior Manager, Applied Field Engineering - Ai/ml Product Specialist

Snowflake Snowflake · Data AI · NJ, United States · Remote · Solution Engineering

Seeking a Manager, Applied Field Engineering - AI/ML Product Specialist to lead a team of engineers focused on Generative AI, Machine Learning, and Advanced Analytics. Responsibilities include coaching the team through technical sales engagements, driving customer consumption of Snowflake's AI/ML capabilities, providing guidance on customer architectures, and aggregating field insights to inform product roadmap discussions. The role also involves team leadership, recruitment, and development.

What you'd actually do

  1. Drive team performance toward Consumption Activation — ensuring customers successfully move workloads into production and realize contracted credit value
  2. Coach AFEs on technical sales engagement best practices, helping them identify and prioritize high-impact opportunities
  3. Aggregate and communicate field insights to senior leadership; surface recurring product gaps and customer blockers to inform roadmap discussions
  4. Recruit, onboard, and develop a team of Applied Field Engineers, with a focus on technical growth and performance management
  5. Build a culture of Technical Sales excellence where AFEs serve as trusted advisors to customers throughout the sales and post-sales lifecycle

Skills

Required

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

Nice to have

  • AI-native thinkers
  • innate curiosity
  • low-ego individuals
  • experimental mindset

What the JD emphasized

  • AI/ML capabilities
  • Generative AI
  • Machine Learning
  • Advanced Analytics
  • Consumption-based models
  • Technical credibility
  • GenAI/LLMs
  • Machine Learning
  • Data Engineering
  • Cloud Data Architecture

Other signals

  • AI/ML capabilities
  • Generative AI
  • Machine Learning
  • Advanced Analytics
  • consumption activation
  • technical sales engagements
  • customer architectures
  • product feedback
  • roadmap discussions
  • technical growth
  • performance management
  • trusted advisors