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Job Location : Arlington, VA (Onsite/Hybrid from Day 1)
Job Description
We are seeking a highly experienced Snowflake Architect with deep expertise in Snowflake Cortex and Agentic AI to lead and guide a team of approximately 25 engineers and AI practitioners in delivering enterprise-scale Agentic AI solutions. This role requires a hands-on architect who can quickly assess existing AI agents, identify strengths and gaps, recommend improvements, and establish best practices to accelerate successful AI adoption across the organization.
The ideal candidate will combine strong Snowflake architecture experience with practical expertise in Cortex AI capabilities, RAG architectures, AI agents, semantic search, and enterprise AI solution delivery.
Key Responsibilities
- Lead end-to-end architecture and solution design for Snowflake-based data, analytics, and AI platforms.
- Provide technical leadership and mentorship to a team of 25+ engineers, architects, and developers delivering Agentic AI solutions.
- Assess existing AI agents and Agentic AI implementations, identifying what is working well, what is not, and providing recommendations for optimization and scalability.
- Establish architectural standards, governance frameworks, and best practices for building, deploying, and managing AI agents.
- Architect and implement AI-powered solutions leveraging Snowflake Cortex capabilities, including Cortex Search, Cortex Analyst, LLM Functions, Document AI, vector embeddings, semantic search, and RAG patterns.
- Drive the adoption of Agentic AI frameworks and guide teams on designing autonomous, intelligent, and business-aligned AI workflows.
- Design and optimize Snowflake data warehouses, data lakes, and lakehouse architectures for analytics, reporting, AI, and machine learning workloads.
- Design ingestion frameworks including batch, streaming, Snowpipe, and real-time processing solutions.
- Develop AI-ready data foundations, semantic layers, and reusable data products that support advanced analytics and Generative AI use cases.
- Collaborate with Data Engineers, Data Scientists, Product Owners, Business Stakeholders, and AI teams to align technical solutions with business objectives.
- Define performance metrics, evaluation criteria, and governance processes for AI agents and enterprise AI solutions.