Senior Manager, Applied Field Engineering (AI/ML)

Location: Menlo Park, California; Boston, Massachusetts; or New York, New York, United States

Salary: $207,000–$271,688 per year

Company

Snowflake provides a cloud data platform with AI/ML capabilities for enterprise customers.

What you will do

• Lead and develop a team of Applied Field Engineers specializing in Snowflake’s AI/ML product portfolio.
• Drive customer adoption and measurable business outcomes for AI/ML workloads built and scaled on Snowflake.
• Coach engineers on product positioning, customer architecture reviews, and long-term platform value.
• Own the field-to-product feedback loop by synthesizing customer insights, product gaps, and adoption blockers.
• Partner with Product Management, Engineering, Product Marketing, and Sales leadership on roadmap priorities, enablement, and strategic accounts.
• Participate in product beta programs, early-access initiatives, and design partnerships.

Requirements

• 8+ years of experience in technical field roles such as pre-sales, solutions engineering, product specialization, or technical consulting.
• 2+ years of people-management experience leading technical or product specialist teams.
• Hands-on expertise in at least two areas including LLMs/GenAI, ML model development and deployment, MLOps, Snowflake Cortex, or cloud-native AI/ML platforms.
• Experience influencing product roadmaps and translating customer feedback into product requirements.
• Ability to engage VP- and Director-level stakeholders on technical capabilities and business outcomes.
• University degree in computer science, engineering, mathematics, or a related field, or equivalent experience.

Culture & Benefits

• Work in a fast-moving, experimental environment focused on impact, innovation, and collaboration.
• Partner with deeply technical specialists who combine product expertise with customer empathy.
• Contribute to Snowflake’s evolving AI/ML product surface, including Cortex capabilities, agent frameworks, and ML platform features.
• Follow company confidentiality and data-security standards when handling sensitive customer information.