Sr Manager, Applied Field Engineering - AI/ML
Snowflake is hiring a Sr Manager, Applied Field Engineering - AI/ML in Menlo Park, United States. It pays $207k-$272k a year and Level rates it ; you can apply on Snowflake.
Level's read on this job
- On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Cortex AI, AI agents and MLOps among its tools and skills.
- Level classes it as a lead role.
- Snowflake has 354 other open roles on Level.
AI in this role
Lead a team of applied field engineers driving adoption of Snowflake's AI/ML product portfolio and agentic workflows.
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
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 Senior Manager, Applied Field Engineering — AI/ML Product Specialists to lead a high-performing team of AI/ML specialists at the intersection of product, field, and customer success.
In this hands-on leadership role, you will manage a team of Applied Field Engineers who are deep practitioners in Snowflake's AI/ML product portfolio — including Cortex AI, ML modeling, and agentic workflows. You will drive product adoption and customer outcomes, ensuring customers move beyond initial activation to unlock the full depth of Snowflake's AI/ML capabilities. Critically, you will serve as a strategic bridge between the field and Snowflake's product organization — translating customer experience into structured product insight that directly shapes roadmap priorities. You will work closely with Product Management, Engineering, and Sales leadership to ensure Snowflake builds the right things and customers realize their full potential.
Responsibilities & Focus Areas
Product Adoption & Customer Outcomes:
Drive team performance toward meaningful product adoption — ensuring customers successfully build and scale AI/ML workloads on Snowflake and realize measurable business outcomes
Coach AFEs to lead with product depth, helping customers understand how Snowflake's AI/ML capabilities map to their use cases and data strategy
Review customer architectures with a product lens, guiding teams toward patterns that maximize long-term platform value and minimize technical debt
Actively engage in strategic customer conversations as a player/coach, modeling how to position Snowflake's AI/ML products against customer requirements and competitive alternatives
Product Partnership & Roadmap Influence:
Own the field-to-product feedback loop for AI/ML: systematically gather, synthesize, and prioritize customer insights, product gaps, and adoption blockers from your team
Maintain direct relationships with AI/ML Product Management and Engineering counterparts — bring structured field signal into roadmap discussions and represent customer needs in product planning
Partner with Product Marketing to ensure field-facing materials accurately reflect current product capabilities, and flag gaps where messaging and product reality diverge
Participate in product beta programs, early access initiatives, and design partnerships — positioning your team and strategic customers as input sources for new AI/ML features
Partner with Sales leadership to align technical resources to pipeline and key account priorities where product depth is the differentiating factor
Team Leadership & Development:
Recruit, onboard, and develop a team of Applied Field Engineers with exceptional AI/ML product depth — the bar is practitioners who have built with these technologies, not just presented them
Build a team culture where AFEs are recognized as product experts and trusted advisors, equally comfortable in a product roadmap discussion as in a customer architecture review
Conduct regular 1:1s, provide ongoing feedback, and invest actively in each AFE's technical and product knowledge development
Run internal enablement to keep the team current on Snowflake's evolving AI/ML product surface, including new Cortex capabilities, agent frameworks, and ML platform features
On day one we will expect you to have:
8+ years of experience in technical field roles (pre-sales, solutions engineering, product specialist, or technical consulting) with increasing scope and impact
2+ years of people management experience leading technical specialist or product specialist teams
Deep product intuition: demonstrated experience working closely with product management — influencing roadmaps, contributing structured customer feedback, and translating field experience into product requirements
Hands-on AI/ML product expertise: practical depth in at least two of the following — Large Language Models / GenAI, ML model development and deployment, MLOps, Snowflake Cortex, or cloud-native AI/ML platforms
Customer outcome orientation: ability to drive product adoption and measurable customer value, not just initial activation or deal closure
Executive presence: confident engaging VP and Director-level stakeholders on both technical product capabilities and strategic business outcomes
University degree in computer science, engineering, mathematics, or a related field (or equivalent experience)
About Our Team
Our Applied Field Engineering team consists of deeply technical specialists who combine product expertise with customer empathy. We are passionate about ensuring Snowflake's AI/ML capabilities reach their full potential in production — and that what we learn in the field makes Snowflake's products better.
Why Snowflake
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
Every Snowflake employee is expected to follow the company's confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company's data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
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
How we rate this
Sr Manager, Applied Field Engineering - AI/ML at Snowflake rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where ai ml was part of your work. What did you do?
- Tell me about a project where product management was part of your work. What did you do?
- Tell me about a project where customer success was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, ML Ops, AI ML, Product Management, and Customer Success. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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