Snowflake3 days ago
Старший менеджер, прикладная инженерия в области AI/ML
Salary not specified
MARKET
15,900 ₽median for this role
Data Scientist · 115 jobs with disclosed pay
5,000half of the offers: 12,796–20,50043,793
The employer didn't disclose pay — compare with the market yourself.
Полная занятостьUS-CA-Menlo Park
Responsibilities
- 01Drive team performance toward meaningful product adoption — ensuring customers successfully build and scale AI/ML workloads on Snowflake and realize measurable business outcomes
- 02Coach AFEs to lead with product depth, helping customers understand how Snowflake's AI/ML capabilities map to their use cases and data strategy
- 03Review customer architectures with a product lens, guiding teams toward patterns that maximize long-term platform value and minimize technical debt
- 04Actively engage in strategic customer conversations as a player/coach, modeling how to position Snowflake's AI/ML products against customer requirements and competitive alternatives
- 05Own the field-to-product feedback loop for AI/ML: systematically gather, synthesize, and prioritize customer insights, product gaps, and adoption blockers from your team
- 06Maintain direct relationships with AI/ML Product Management and Engineering counterparts — bring structured field signal into roadmap discussions and represent customer needs in product planning
- 07Partner with Product Marketing to ensure field-facing materials accurately reflect current product capabilities, and flag gaps where messaging and product reality diverge
- 08Participate in product beta programs, early access initiatives, and design partnerships — positioning your team and strategic customers as input sources for new AI/ML features
- 09Partner with Sales leadership to align technical resources to pipeline and key account priorities where product depth is the differentiating factor
- 10Recruit, 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
- 11Build 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
- 12Conduct regular 1:1s, provide ongoing feedback, and invest actively in each AFE's technical and product knowledge development
- 13Run 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
Requirements
- 018+ years of experience in technical field roles (pre-sales, solutions engineering, product specialist, or technical consulting) with increasing scope and impact
- 022+ years of people management experience leading technical specialist or product specialist teams
- 03Deep product intuition: demonstrated experience working closely with product management — influencing roadmaps, contributing structured customer feedback, and translating field experience into product requirements
- 04Hands-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
- 05Customer outcome orientation: ability to drive product adoption and measurable customer value, not just initial activation or deal closure
- 06Executive presence: confident engaging VP and Director-level stakeholders on both technical product capabilities and strategic business outcomes
- 07University degree in computer science, engineering, mathematics, or a related field (or equivalent experience)