Associate Principal Engineer - Snowflake AI Architect
Job Description
Snowflake Cortex AI
• 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.
Data Platform & Engineering
• 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.
Governance, Security & Standards
• Establish and enforce architectural standards, best practices, and governance frameworks for Snowflake and Cortex AI implementations.
• Ensure solutions meet data security, privacy, compliance, and governance requirements — particularly in regulated environments such as financial services.
• Conduct architecture reviews, design reviews, and code reviews across data engineering teams.
Leadership & Stakeholder Engagement
• Partner with senior business stakeholders, data scientists, and engineering leaders to identify high-value AI/ML use cases and translate requirements into deliverable architecture.
• Mentor and guide senior data engineers, analysts, and architects on Snowflake and AI best practices.
• Stay current with Snowflake product releases and Cortex AI advancements, and proactively recommend adoption where it creates measurable value.
Requirements
Department: Engineering
Function: Information Technology
Experience Level: Not Applicable