Sr Manager, Applied Field Engineering - AI/ML
Manager · Manager · Full Time
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Role
What you'll do.
Senior Manager leading a high-performing Applied Field Engineering team at Snowflake, responsible for driving AI/ML product adoption and customer outcomes while serving as a strategic bridge between field operations and product management. This role requires deep technical expertise in Large Language Models, ML model development, MLOps, and cloud-native AI platforms, combined with 8+ years of technical field experience and proven people management capabilities to influence product roadmaps and ensure customers unlock the full potential of Snowflake's Cortex AI and agentic workflow capabilities.
Responsibilities
- Drive Product Adoption and Customer Outcomes: Lead team performance toward meaningful adoption of Snowflake's AI/ML capabilities, ensuring customers successfully build and scale AI/ML workloads while realizing measurable business outcomes. Coach Applied Field Engineers to lead with deep product expertise, helping customers understand how Snowflake's AI/ML capabilities align with their use cases and data strategies.
- Manage Field-to-Product Feedback Loop: 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 to bring structured field signal into roadmap discussions and represent customer needs in product planning cycles.
- Guide Strategic Customer Architecture Reviews: 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.
- Recruit and Develop Applied Field Engineering Team: Build and manage a team of Applied Field Engineers with exceptional AI/ML product depth—practitioners who have hands-on experience building with these technologies. Conduct regular 1:1s, provide ongoing feedback, and invest actively in each team member's technical and product knowledge development through customized enablement.
- Enable Team on Evolving AI/ML Capabilities: Run internal enablement programs to keep the team current on Snowflake's evolving AI/ML product surface, including new Cortex capabilities, agent frameworks, ML platform features, and emerging best practices in agentic enterprise workflows.
- Partner with Cross-Functional Leadership: Collaborate with Product Marketing to ensure field-facing materials accurately reflect current product capabilities and flag gaps where messaging diverges from product reality. Partner with Sales leadership to align technical resources to pipeline and key account priorities where product depth is the differentiating factor.
- Participate in Product Innovation Programs: Engage in product beta programs, early access initiatives, and design partnerships, positioning your team and strategic customers as input sources for new AI/ML features and capabilities. Drive structured feedback from field experience back into product development cycles.
- Build High-Performance Team Culture: Create a team culture where Applied Field Engineers are recognized as product experts and trusted advisors, equally comfortable in product roadmap discussions as in customer architecture reviews. Foster an environment that attracts and retains deep technical talent with AI/ML specialization.
Qualifications
What we look for.
Technical
Large Language Models and Generative AI
Demonstrated hands-on expertise building, deploying, or optimizing LLM-based applications, including prompt engineering, RAG architectures, and fine-tuning techniques. Deep understanding of how LLMs integrate into enterprise data platforms and customer workflows.
ML Model Development and Deployment
Practical experience developing machine learning models from training through production deployment. Understanding of model versioning, feature engineering, model evaluation, and real-world ML deployment challenges in cloud environments.
MLOps and Model Governance
Expertise in MLOps practices including model monitoring, retraining pipelines, experiment tracking, and governance frameworks. Familiarity with tools and platforms that manage the full ML lifecycle in production environments.
Cloud-Native AI/ML Platforms
In-depth knowledge of cloud-native AI/ML platforms, including Snowflake Cortex, and understanding of how these platforms enable enterprise-scale AI/ML deployments. Experience with cloud infrastructure, data warehousing, and AI service integration.
Solution Architecture and System Design
Ability to design scalable AI/ML solutions that address complex customer requirements. Understanding of architecture patterns, integration strategies, and technical trade-offs in enterprise AI/ML implementations.
Education
Computer Science or Engineering Degree
University degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent professional experience demonstrating equivalent technical depth and knowledge.
Experience
Technical Field Engineering Leadership
8+ years of experience in technical field roles such as pre-sales engineering, solutions engineering, product specialist roles, or technical consulting with increasing scope and impact demonstrating career progression and expanding responsibility.
People Management and Team Leadership
2+ years of direct people management experience leading technical specialist teams, product specialist teams, or field engineering organizations. Proven ability to recruit, develop, and retain high-performing technical talent.
Product Management and Roadmap Influence
Demonstrated experience working closely with product management teams, influencing roadmaps through structured customer feedback, and translating field experience into actionable product requirements. Evidence of shaping product direction based on customer insights.
Customer Outcome Orientation and Product Adoption
Proven track record driving product adoption and measurable customer value beyond initial activation or deal closure. Experience moving customers from early adoption to production-scale implementations with clear business impact.
Executive Stakeholder Engagement
Demonstrated executive presence and confidence engaging VP and Director-level stakeholders on both technical product capabilities and strategic business outcomes. Ability to communicate complex technical concepts to non-technical executives.
Skills
Required
AI/ML Product Expertise
Deep hands-on experience with at least two AI/ML domains including Large Language Models/GenAI, ML model development and deployment, MLOps, Snowflake Cortex, or cloud-native AI/ML platforms.
Technical Leadership and Team Management
Ability to lead, mentor, and develop high-performing teams of technical specialists. Skill in building team culture that attracts practitioners with deep AI/ML expertise and retains top talent.
Product Strategy and Roadmap Influence
Capability to gather structured customer feedback, synthesize insights into product requirements, and effectively advocate for roadmap priorities. Understanding of product development processes and cross-functional collaboration.
Customer Success and Outcome Orientation
Expertise in driving customer adoption, measuring business outcomes, and scaling implementations from pilot to production. Ability to move beyond initial activation to unlock full platform value.
Solutions Architecture and Design
Ability to review complex customer architectures, identify optimization opportunities, and guide teams toward scalable, maintainable technical patterns that maximize long-term platform value.
Executive Communication
Strong communication skills for engaging C-suite and VP-level stakeholders on technical product capabilities and strategic business initiatives. Ability to translate between technical and business contexts.
Field Engineering and Pre-Sales Expertise
Deep knowledge of technical field operations, customer requirements gathering, solution positioning, and competitive differentiation. Understanding of how field teams drive deal acceleration and customer success.
Preferred
Agentic AI and Autonomous Systems Experience
Nice to haveHands-on experience building or deploying agentic systems, autonomous workflows, or AI agents in production environments. Understanding of agent frameworks, orchestration, and enterprise agentic architectures.
Data Warehouse and Data Platform Experience
Nice to haveExperience with data warehousing platforms, modern data stacks, or data lake architectures. Understanding of how AI/ML integrates with data infrastructure and enterprise analytics platforms.
Enterprise Software Sales Engineering
Nice to haveBackground in enterprise technology sales engineering or field roles focused on complex, multi-stakeholder deals. Understanding of enterprise buying cycles and organizational decision-making processes.
Product Beta and Early Access Program Leadership
Nice to haveExperience leading or managing product beta programs, early access initiatives, or design partnerships. Track record of gathering structured feedback from early adopter customers and translating it to product insights.
Cross-Functional Collaboration and Matrix Management
Nice to haveProven ability to influence across organizational boundaries, collaborate with product engineering and sales leadership, and drive alignment on shared priorities without direct authority.
Technical Enablement and Curriculum Development
Nice to haveExperience building and scaling technical training programs, enablement curricula, or certification programs that keep teams current on evolving product capabilities and best practices.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 207,000 – 271,688
Equity·Stock options
Benefits
Competitive Equity and Stock Options
Participation in Snowflake's equity programs as a senior leadership team member, aligning your financial interests with company growth and long-term value creation.
Comprehensive Health and Wellness Coverage
Medical, dental, and vision insurance with multiple plan options. Access to wellness programs, mental health support, and preventive care resources for you and your family.
Retirement Planning and Financial Security
401(k) retirement plan with employer matching contributions. Access to financial planning resources and retirement consulting services to support long-term financial security.
Generous Time Off and Flexibility
Flexible paid time off policies, paid parental leave, sabbatical programs, and flexible work arrangements to support work-life balance and personal well-being.
Professional Development and Career Growth
Tuition reimbursement for relevant certifications and advanced degrees. Access to industry conferences, training programs, and mentorship opportunities to advance your technical and leadership skills.
Technology and Equipment
Latest laptops, development tools, and software licenses to support your work. Home office stipend and equipment allowances for remote or flexible work arrangements.
Commuter and Transportation Benefits
Pre-tax commuter benefits, transit subsidies, or parking support depending on location. Support for employees commuting to Snowflake offices or working hybrid arrangements.
Learning and Development Resources
Access to online learning platforms, technical courses, and leadership development programs. Support for industry certifications and continuing education in AI/ML and emerging technologies.
Full posting
Original listing.
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
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