| Overview The Senior Data & AI Solutions Architect is a strategic, hands-on technical expert responsible for designing and delivering enterprise data and artificial intelligence solutions across the core business lines of Life Insurance, Investments, Membership and Charities. This is a senior level individual contributor role who will be responsible for operating as a domain authority and trusted technical partner driving outcomes through influence, collaboration, and deep expertise. Reporting directly to the Director of Applied AI & Data Science, this role partners closely with business leaders, data analysts, data movement engineers, infrastructure teams, and peer architects to translate business needs into architectures that are secure, governed, and built to scale. The Senior Data & AI Solutions Architect plays a critical role in continuing to modernize the data landscape including bridging legacy mainframe and DB2 platforms with a cloud and AI enabled ecosystem that includes Snowflake, PostgreSQL, Talend, Microsoft Copilot, Snowflake Cortex, and enterprise large language models. This foundation is essential to enabling Deep Research LLM and agentic AI capabilities across the organization. Core Responsibilities " Define and govern enterprise Data & AI architecture across legacy, cloud, and AI native platforms " Architect hybrid data integration across mainframe, DB2, Snowflake, Postgres, Talend, and event streaming " Design and deliver LLM and agentic AI solutions using Snowflake Cortex, Azure AI Foundry, Azure OpenAI Service, Copilot Studio, and orchestration frameworks " Establish RAG, vector database, and embedding strategies for enterprise research and analytics " Coordinate the continual modernization of ETL and Lakehouse architecture " Enable Snowflake governance: RBAC, dynamic masking, row level security, encryption " Ensure compliance with OSFI, SOX, NAIC, PIPEDA/GDPR, SEC/state insurance regulations " Partner with business, risk, compliance, legal, IT, Information Security and vendors as the lead technical advisor Skills Qualifications Required: " 3+ years hands on Snowflake experience (Snowpark, Cortex, data sharing) " 3+ years delivering production LLM / GenAI solutions (RAG, agents, fine tuning) " Proven legacy to cloud migration experience involving IBM DB2 or equivalent " Experience with Talend, modern data integration, and real time ingestion " Knowledge of relational (e.g., PostgreSQL), NoSQL, NewSQL, and vector/LLM databases " Demonstrated experience with legacy-to-cloud data migration involving IBM DB2 or equivalent mainframe/relational systems " Proven delivery of agentic AI systems or multi-model orchestration pipelines in enterprise environments Education Required: " 12+ years in data architecture, data engineering, or enterprise architecture " 5+ years in financial services (life insurance, annuities, investments preferred) |