Director, Applied Field Engineering - AI/ML Product Specialist

Snowflake2 weeks ago

Location

US-WA-Bellevue

Type

Full Time

Salary

USD 231,000 – 303,188

Level

Director

Role

Engineering Manager

Posted

Feb 23, 2026

Full TimeDirector

The role

Summary

This Director role leads a specialized team of Applied Field Engineers focused on AI/ML and advanced analytics at Snowflake. The position combines technical sales excellence with strategic product influence, requiring expertise in GenAI, machine learning, and data architecture. The role demands 15+ years of pre-sales experience, 4+ years of management experience, and proven success with consumption-based models.

What you'll do

Technical Sales Leadership: Drive consumption activation and ensure customers successfully move workloads into production while optimizing technical sales cycles for high-impact opportunities

Product Strategy and Influence: Identify product gaps, shape product direction based on AI/ML trends, and partner with Product Management to influence roadmaps

Team Management: Recruit, hire, and manage a high-performing team of Applied Field Engineers while cultivating a culture of technical sales excellence

Architectural Leadership: Ensure architectures are optimized for long-term growth and business value while preventing technical debt that could stall future consumption

Executive Engagement: Lead compelling architectural discussions and presentations at executive roundtables and community events as a player/coach

Strategic Alignment: Collaborate with Sales Leadership to align technical resources with regional revenue targets and key account plans

Community Development: Establish and scale internal Communities of Practice to elevate team skills across all segments and regions within the Americas

What we look for

Technical

AI/ML ExpertiseExecutive-level expertise in GenAI/LLMs, Machine Learning, Data Engineering, or Cloud Data Architecture with deep technical authority

Consumption-based ModelsProven track record driving actual activation and usage of software services beyond just bookings

Strategic Product InfluenceDemonstrated ability to translate complex customer challenges into actionable product requirements and influence engineering roadmaps

Executive PresenceProven ability to advise C-level executives on future-state technical architectures and business ROI of AI/ML investments

Education

University DegreeBachelor's degree in computer science, engineering, mathematics, or related fields (or equivalent experience)

Experience

Industry Experience15+ years of experience in pre-sales, technical sales, or technical consulting capacity

Management Experience4+ years of people management experience, preferably leading specialized technical overlay teams

Skills

Required skills

Technical SalesExpertise in technical pre-sales, solution architecture, and customer-facing technical presentations

Team LeadershipProven ability to recruit, manage, and develop high-performing technical teams

AI/ML Domain ExpertiseDeep knowledge in at least two areas: GenAI/LLMs, Machine Learning, Data Engineering, or Cloud Data Architecture

Executive CommunicationAbility to communicate complex technical concepts to C-level executives and influence strategic decisions

Product ManagementExperience translating customer requirements into product features and influencing engineering roadmaps

Nice to have

Cloud ArchitectureExperience designing and implementing large-scale cloud data architectures

Consumption ModelsUnderstanding of usage-based pricing and driving customer adoption beyond initial technical validation

Community BuildingExperience establishing and scaling technical communities of practice

Industry SpeakingExperience presenting at conferences and industry events on AI/ML and data topics

Compensation & benefits

Salary

USD 231,000 – 303,188 (annual)

Stock options

Available

Benefits

Health Insurance

Comprehensive medical, dental, and vision coverage for employees and their families

Equity Participation

Stock options and equity participation in Snowflake's growth as a publicly traded company

Professional Development

Investment in continuous learning, conference attendance, and certification programs

Flexible Work Environment

Remote-friendly culture with flexible work arrangements and modern collaboration tools

Innovation Time

Dedicated time for exploring new technologies and contributing to Snowflake's innovation culture

Interview process

1
Initial Screening — Phone or video call with talent acquisition focusing on experience, leadership background, and cultural fit
2
Hiring Manager Interview — Deep dive discussion with the hiring manager on technical sales experience, team leadership, and strategic vision
3
Technical Leadership Panel — Panel interview with senior technical leaders assessing AI/ML expertise, architectural thinking, and product influence capabilities
4
Executive Presentation — Strategic presentation to senior leadership demonstrating executive presence, vision for the team, and understanding of consumption models
5
Team and Peer Interviews — Meetings with potential team members and cross-functional partners to assess collaboration and management style
6
Final Executive Interview — Final interview with senior executive focusing on strategic alignment, cultural fit, and long-term vision for the role