Snowflake

SaaS

SeniorAI/MLArchitect,AppliedFieldEngineering

$165–217k New York, New York, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior AI/ML Architect, Applied Field Engineering at Snowflake. Skills: AI/ML, Generative AI, Cloud solutions, Field engineering. Position AI and ML features. Position value to stakeholders”

What You'll Achieve.

Ensure successful execution; Ensure customer adoption

Industry & Context.

SaaS
Problems you'll solve

Solve problems; Accelerate impact

What They're Looking For.

Must Have

5+ years experience building, 5+ years deploying machine learning, 5+ years generative AI solutions, Familiarity generative AI techniques, Knowledge generative AI techniques, Deep knowledge Python, Knowledge common ML packages, Knowledge data engineering tools, Knowledge data engineering technologies, Presentation skills technical audiences, Presentation skills executive audiences, Bachelor's Degree required

Nice to Have

Masters Degree in computer science, Masters Degree in engineering, Masters Degree in mathematics, Equivalent experience preferred, Working knowledge LLM ecosystem, Experience large-scale infrastructure-as-a-service, Understanding large-scale infrastructure-as-a-service, 1+ years practical Snowflake experience, Knowledge large-scale database technology, Experience large-scale database technology

What You'll Do.

Position AI and ML features

Position value to stakeholders

Partner with account teams

Partner with customer champions

Drive POCs to success

Prove value of capabilities

Provide executive readouts

Develop business value cases

Collaborate with product teams

Collaborate with engineering teams

Influence AI roadmaps

Influence ML roadmaps

Present at conferences

Create technical collateral

Influence selling assets

Tailor selling assets

Maintain selling assets

Develop customer presentations

Develop demonstrations

Develop customer stories

How You'll Work.

Team & Collaboration

Cross-functional teams; Product teams; Engineering teams; Field organization; Account teams; Customer champions

Communication Scope

Executive readouts; Business value cases; Customer presentations; Demonstrations

Full Job Description

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. Our Solution Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud. This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions. IN THIS ROLE YOU WILL GET TO: - Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas. - Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases. - Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback. - Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos. - Influence, tailor and maintain Sales Engineering AI and ML selling asset

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