Snowflake AI Solutions Architect

We are seeking an experienced Snowflake AI Solutions Architect with strong expertise in Snowflake architecture, enterprise security, Generative AI, RAG, and multi-agent AI solutions. The ideal candidate will have hands‑on experience designing and implementing scalable Snowflake‑based data and AI platforms in production environments.

Key Responsibilities

• Architect and implement enterprise-scale Snowflake data and AI solutions .
• Lead Snowflake architecture, platform design, performance optimization, and technical implementation.
• Design and implement RBAC (Role-Based Access Control) and Row-Level Security (RLS) in production Snowflake environments.
• Develop scalable data processing and application workloads using Snowpark and Python .
• Design and implement GenAI solutions using Snowflake Cortex , including Cortex Search and Cortex Analyst .
• Build enterprise Retrieval-Augmented Generation (RAG) solutions using vector databases, embeddings, semantic search, and LLMs.
• Develop AI applications and orchestration workflows using LangChain, LangGraph, and/or Semantic Kernel .
• Architect multi-agent AI systems , including agent orchestration, tool integration, workflow management, and inter-agent communication.
• Design secure integrations between Snowflake, enterprise applications, APIs, LLMs, and AI services.
• Define architecture patterns and standards for AI/ML, Generative AI, and Agentic AI solutions .
• Collaborate with data engineering, AI/ML, security, cloud, and application teams to translate business requirements into technical solutions.
• Establish best practices around Snowflake security, governance, scalability, performance, and cost optimization.
• Provide technical leadership, architecture guidance, solution reviews, and implementation support.

Required Skills

• 10–15 years of overall IT/data engineering and architecture experience.
• Strong experience as a Snowflake Architect / Technical Lead .
• Advanced hands‑on expertise with Snowflake architecture and development .
• Production implementation experience with RBAC and Row‑Level Security (RLS) .
• Strong hands‑on experience with Snowpark .
• Strong programming experience with Python .
• Hands‑on experience with Snowflake Cortex Search and Cortex Analyst .
• Experience with LangChain, LangGraph, and/or Semantic Kernel .
• Strong understanding of Vector Databases, embeddings, semantic search, and RAG architecture .
• Experience designing and implementing Multi-Agent AI Architecture .
• Strong knowledge of LLMs, Generative AI, Agentic AI, prompt engineering, and AI solution design .