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Create Advanced Analytics/Decision Intelligence driving predictive analytics, propensity
GenAI/Agent Engineering that is essential to the enterprise agent strategy – MCP, RAG
Architect and deploy enterprise-grade multi-agent AI systems for complex, multi-step workflows
Design internal AI tools and agents (e.g., AI Finance Bot, domain-specific LLM applications) and
Drive Data Governance & AI Readiness – quality, lineage, observability, catalog, access
Provide business context to a Semantic & Context Architecture with metrics layer, business

12+ years of leadership experience in data and software engineering environments, with at least 5
Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI/ML, Math or a highly
Strong familiarity with core technical stack - cloud data ecosystems (e.g., Snowflake, Databricks
Experience moving to modern data architecture environment, with deep Datawarehouse/lakehouse (AWS
Proven experience with AI/ML engineering and success deploying ML models into production, feature
Exceptional ability to translate complex agentic systems, context-engineering strategies, and

AVP, Data, Analytics & AI Engineering

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