Associate Principal Engineer - Snowflake AI Architect

Architect and lead the design of enterprise-scale Snowflake Cortex AI solutions, including Cortex AISQL, Cortex Analyst, Cortex Search, Cortex Agents, Document AI, and fine-tuning.

Design and implement Retrieval-Augmented Generation (RAG) pipelines using Cortex Search, vector embeddings, and appropriate chunking, retrieval, and reranking strategies.

Build conversational analytics and text-to-SQL experiences using Cortex Analyst over governed semantic models, with defined accuracy and evaluation criteria.

Apply Cortex LLM functions (COMPLETE, SUMMARIZE, SENTIMENT, TRANSLATE, EXTRACT_ANSWER, CLASSIFY) within SQL and Python workflows where they are the right tool for the job.

Configure Cortex Sense to assemble shared business context that grounds CoWork and CoCo agents for higher out-of-the-box accuracy.

Expose Cortex Agents, semantic views, and search services as reusable tools via Snowflake-managed MCP servers for consumption across MCP-compatible clients.

Enable teams to build with Snowflake CoCo — the Snowflake-native, data-aware AI coding agent — to accelerate data engineering, ML pipelines, and agent development in ways that respect catalog, lineage, and RBAC.

Lead integration of vector search and embedding models into AI-powered data workflows.

Define and own the technical architecture and multi-year roadmap for Snowflake-based AI and data platforms.

Lead the design of scalable data pipelines, data models, and warehousing solutions optimized for both performance and cost.

Drive adoption of Snowpark (Python/Java/Scala) for advanced data engineering and ML workflows.

Develop and deploy models using Snowflake ML, Snowpark, and Model Registry; operationalize feature engineering and inference at scale.

Oversee pipeline orchestration using Airflow, dbt, Matillion, or comparable tooling.