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 Architecture, Generative AI, Field Engineering, Solution Engineering. Be technical expert. Position AI/ML features”

What You'll Achieve.

Achieve technical wins; Prove value of Snowflake capabilities

Industry & Context.

SaaS
Problems you'll solve

Solve problems; Accelerate impact

What They're Looking For.

Must Have

5+ years building ML solutions, 5+ years deploying ML solutions, 5+ years building generative AI solutions, 5+ years deploying generative AI solutions, Familiarity with RAG, Familiarity with few shot learning, Familiarity with prompt engineering, Familiarity with fine-tuning, Deep knowledge of Python, Knowledge of LangChain, Knowledge of pandas, Knowledge of sklearn, Knowledge of PyTorch, Knowledge of dbt, Knowledge of Airflow, Knowledge of Spark, Presentation skills to technical audiences, Presentation skills to executive audiences

Nice to Have

Masters Degree in computer science, Masters Degree in engineering, Masters Degree in mathematics, Equivalent experience to Masters Degree, Working knowledge of LangChain, Working knowledge of LlamaIndex, Working knowledge of OSS packages, 1+ years of practical Snowflake experience, Knowledge of large-scale database technology, Experience with large-scale database technology

What You'll Do.

Position AI/ML features

Partner with account teams

Drive POCs to success

Prove value of capabilities

Provide executive readouts

Provide business value cases

Collaborate with product teams

Collaborate with engineering teams

Influence AI/ML roadmaps

Create technical collateral

Influence selling assets

Tailor selling assets

Maintain selling assets

Create customer presentations

Create customer demonstrations

Create customer stories

How You'll Work.

Team & Collaboration

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

Communication Scope

Technical presentations; Executive presentations; Whiteboarding sessions; Formal readouts; 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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