Description

• Act as the onsite technical lead, engaging directly with client business, data and technology stakeholders.
• Assess the client's current Snowflake estate and existing AI/agent implementations, then define a roadmap to scale them to enterprise level.
• Run discovery workshops to identify, prioritise and size AI agent use cases.
• Define the target architecture for an enterprise agentic AI platform using Snowflake-native capabilities.
• Design reusable architecture patterns, frameworks and standards that let multiple agents be delivered repeatably.
• Lead the semantic layer and knowledge-modelling approach so that business context stays consistent across AI solutions.
• Design security, access control and data governance for AI workloads.
• Define evaluation, observability, Responsible AI and cost-governance practices for production AI solutions.
• Present and defend architecture decisions to senior client stakeholders.
• Guide delivery teams, mentor engineers, and support scoping and estimation for follow-on work.

Must-Have Skills

• 15+ years of experience in data and analytics, including at least 3 years architecting enterprise platforms on Snowflake.
• Hands-on experience with Snowflake Cortex AI (Cortex Agents, Cortex Analyst, Cortex Search and AI functions) and Semantic Views.
• Strong grasp of agentic AI and GenAI architecture patterns, including RAG, tool orchestration and human-in-the-loop design.
• Expertise in Snowflake security and governance: RBAC, masking and row access policies.
• Experience designing evaluation, monitoring and guardrails for LLM-based solutions.
• Advanced SQL and Python (Snowpark), and CI/CD for Snowflake.
• Strong client-facing communication and presentation skills.
• SnowPro Core certification (COF-C03), and SnowPro Advanced: Architect (ARA-C01) strongly preferred.

Good-to-Have Skills

• SnowPro Specialty: Gen AI certification (GES-C02).
• SnowPro Advanced: Data Engineer (DEA-C02) or Security Engineer (SEA-C01).
• Knowledge of the Model Context Protocol (MCP) and agent interoperability.
• Ontology or knowledge-graph modelling, and data catalog or governance tools.
• Multi-agent frameworks such as LangGraph, Snowpark Container Services or Streamlit in Snowflake.
• Exposure to AWS or Azure and to enterprise integration patterns.
• Experience in BFSI, particularly banking or cards, and familiarity with regulated-industry controls

Key Skills

Education

Bachelor's degree