招聘

Director, Applied Field Engineering - AI/ML Product Specialist
US-WA-Bellevue
·
On-site
·
Full-time
·
1w ago
Required Skills
Technical Sales
Generative AI
Machine Learning
Data Engineering
Cloud Architecture
People Management
Product Strategy
Executive Communication
Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level.
At Snowflake, we empower both enterprises and individuals to reach their full potential. Our culture prioritizes impact, innovation, and collaboration, making Snowflake the ideal place to build ambitious projects, execute quickly, and advance technology — and your career — to the next level.
THE ROLE:
- We are seeking a Director, Applied Field Engineering
- AI/ML Product Specialists to spearhead our thriving and expanding America’s team within the Applied Field Engineering organization.
In this pivotal leadership position, you will manage a team of Applied Field Engineers who are experts in specialized domains, including Generative AI, Machine Learning, and Advanced Analytics.
Your core responsibility will be to guide your team in Technical Sales excellence—securing technical wins while ensuring Consumption Activation. This involves more than just technical validation; you will lead your team in resolving architectural gaps and ensuring that solutions meet critical criteria like reliability and performance. Ultimately, your strategic leadership will be key in defining the team's vision, setting strategic priorities, and shaping product direction by surfacing critical market gaps to our engineering teams.
RESPONSIBILITIES & FOCUS AREAS:
TECHNICAL STRATEGY & CONSUMPTION ACTIVATION:
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Drive Consumption Activation: Shift beyond the "technical win" to ensure customers successfully move workloads into production, directly accelerating the realization of contracted credits.
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Optimize Technical Sales Cycles: Refine engagement models to ensure AFEs are deployed on high-impact opportunities that maximize both TACV (Total Annual Contract Value) and immediate consumption potential.
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Architect for Scale: Ensure architectures are optimized for long-term growth and business value, preventing technical debt that could stall future consumption.
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Serve as a player/coach, leading by example through compelling architectural discussions and presentations at executive roundtables and community events.
PRODUCT DIRECTION & STRATEGIC INFLUENCE:
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Identify Product Gaps: Act as a critical feedback loop between the field and Product Engineering; systematically identify, document, and advocate for features or fixes required to unlock blocked workloads.
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Shape Product Direction: Partner with Product Management to influence the roadmap based on emerging AI/ML trends and "boots on the ground" customer requirements.
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Strategic Alignment: Collaborate closely with Sales Leadership to align technical resources with regional revenue targets and key account plans.
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Community Leadership: Establish and scale internal Communities of Practice to elevate the team's skills across all segments and regions within the Americas.
TEAM LEADERSHIP & DEVELOPMENT:
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Recruit, hire, and manage a high-performing team of Applied Field Engineers (AFEs), prioritizing their ongoing development and performance management.
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Cultivate a culture of Technical Sales excellence, where AFEs act as strategic advisors who bridge the gap between initial technical proof and long-term production value.
ON DAY ONE WE WILL EXPECT YOU TO HAVE:
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15+ years of industry experience in a pre-sales, technical sales, or technical consulting capacity.
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4+ years of people management experience, preferably leading specialized technical overlay teams.
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Proven track record in Consumption-based models: Experience driving not just "bookings," but the actual activation and usage of software services.
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Strategic Product Influence: Demonstrated ability to translate complex customer challenges into actionable product requirements and influence engineering roadmaps.
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Deep Technical Authority: Executive-level expertise in at least two of the following: GenAI/LLMs, Machine Learning, Data Engineering, or Cloud Data Architecture.
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Executive Presence: Proven ability to advise C-level executives on future-state technical architectures and the business ROI of AI/ML investments.
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Education: University degree in computer science, engineering, mathematics, or related fields (or equivalent experience).
ABOUT OUR TEAM:
Our Applied Field Engineering team consists of highly skilled and experienced technical specialists. We are passionate about client and internal stakeholder success, ensuring data is accessible, usable, and valuable to everyone.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com http://careers.snowflake.com
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About Snowflake

Snowflake
Publicsnowflake provides web applications and web hosting services.
1-50
Employees
Zürich
Headquarters
Reviews
3.6
1 reviews
Work Life Balance
3.0
Compensation
3.5
Culture
2.5
Career
3.0
Management
2.0
35%
Recommend to a Friend
Pros
Positive performance reviews and raises
Opportunities to learn new technical skills
Career advancement with promotion
Cons
Role demotion after acquisition
Poor communication regarding promotions
Administrative inefficiencies with title updates
Salary Ranges
3,987 data points
Junior/L3
L3
L4
L5
L6
Mid/L4
Senior/L5
Staff/L6
Junior/L3 · Data Scientist
277 reports
$252,858
total / year
Base
$171,306
Stock
$57,741
Bonus
$23,811
$190,229
$354,557
Interview Experience
8 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 88%
Negative 12%
Interview Process
1
Application Review
2
Resume Screening
3
Initial Phone Screen
4
Technical Phone Screen
5
Technical Coding Round
6
Offer Discussion
Common Questions
Coding/Algorithm
Technical Knowledge
System Design
Behavioral/STAR
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