The architect will define and deliver a reusable, scalable framework that leverages Databricks Mosaic AI, Azure AI Services, Agentic AI, and Large Language Models (Azure OpenAI, Anthropic Claude, Google Gemini) to automate ingestion, mapping, standardization, validation, reconciliation, and onboarding of Bordereaux data from multiple partners.
The role will focus on creating a metadata-driven, configurable onboarding framework capable of handling varying BDX formats while reducing manual mapping, improving data quality, and accelerating partner onboarding.
Required Experience
- 12+ years of Data, Cloud, AI/ML, or Solution Architecture experience.
- 5+ years designing enterprise-scale Azure and Databricks solutions.
- 3+ years architecting Generative AI and Agentic AI solutions.
- Experience building metadata-driven data platforms and onboarding frameworks.
- Experience in Insurance, MGA, Programs, Bordereaux Processing, or Data Modernization initiatives preferred.
Key Responsibilities
AI & Framework Architecture
- Define enterprise architecture for AI-powered Bordereaux onboarding and processing.
- Design reusable frameworks for:
o BDX ingestion
o AI-assisted mapping
o Data standardization
o Business-rule validation
o Data quality monitoring
o Reconciliation workflows
- Establish architecture standards, design principles, and implementation patterns for future onboarding initiatives.
Agentic AI Solution Design
- Design intelligent AI agents capable of:
o Understanding new Bordereaux layouts
o Mapping source columns to target canonical models
o Identifying missing attributes and exceptions
o Recommending transformation rules
o Generating onboarding insights
- Architect Human-in-the-Loop approval workflows for business users.
- Define multi-agent orchestration patterns for ingestion, mapping, validation, exception handling, and approval processes.
Databricks & Azure Architecture
o Databricks Mosaic AI
o Databricks Vector Search
o Delta Lake
o Unity Catalog
o MLflow
o Lakeflow Pipelines
o Azure OpenAI
o Azure Data Lake Storage
- Define Medallion Architecture and metadata-driven processing frameworks.
- Architect scalable, cloud-native solutions to support onboarding of multiple MGA partners and lines of business.
Knowledge & Retrieval Architecture
- Design retrieval frameworks supporting:
o Data dictionaries
o Mapping repositories
o Business rules
o Historical onboarding knowledge
o Transformation patterns
- Implement RAG-based solutions to enable AI-assisted onboarding and decision support.
- Develop semantic knowledge layers to improve mapping accuracy and automation.
Governance & Quality
- Define enterprise AI governance standards.
- Establish guardrails, security controls, lineage, auditability, and compliance controls.
- Define AI evaluation frameworks, model monitoring, and observability standards.
- Implement Responsible AI principles and enterprise data governance.
Leadership & Stakeholder Engagement
- Partner with Business SMEs, Underwriting Teams, Data Architects, and Platform Engineering teams.
- Conduct architecture reviews and design workshops.
- Lead POCs, framework accelerators, and reference implementations.
- Mentor AI Engineers, Data Engineers, and Solution Architects.
