Snowflake AI Engineer

Scottsdale, Arizona, United StatesOnsiteContractPosted 2 months ago

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Role summary

Seeking a Snowflake AI Engineer to build and maintain semantic models, design and deploy Cortex Agents, and configure Snowflake MCP servers. The role involves developing Streamlit apps for interactive AI experiences, defining architecture and governance for scalable agentic AI solutions, and ensuring secure data access. Requires deep hands-on expertise with Snowflake (SQL, Snowpark, performance tuning), proven experience building Cortex Agents end-to-end, and experience with MCP server configuration. Familiarity with LLMs, prompt engineering, and agent design patterns is essential. Python skills for Streamlit app development, data modeling, and knowledge of vector search/RAG are strongly preferred.

Seeking a Snowflake AI Engineer onsite in Scottsdale, AZ!
(Must be US Citizen or Green Card holder | We are unable to partner with third parties at this time)

Responsibilities

Build and maintain semantic models and views optimized for AI and analytics.
Design, develop, and deploy Cortex Agents with robust reasoning, tooling, and guardrails.
Configure and operate the Snowflake MCP server; build custom MCP tools for business workflows.
Develop Streamlit apps in Snowflake that integrate with agents for interactive, AI powered experiences.
Define architecture, governance, and best practices for scalable agentic AI solutions.
Ensure secure, governed access aligned with enterprise RBAC and data policies.
Ability to work independently and translate business needs into technical solutions.

Required Skills

Deep hands on expertise with Snowflake (SQL, Snowpark, performance tuning).
Proven experience building Cortex Agents end to end.
Experience with MCP server configuration and custom tool development.
Solid understanding of LLMs, prompt engineering, and agent design patterns.

Strongly Preferred

Strong Python skills; ability to design and build Streamlit apps inside Snowflake.
Background in data modeling, analytics engineering, or enterprise data architecture.
Familiarity with vector search, RAG, and knowledge graph concepts.

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