AI Architect

AI Architect – Agentic AI / Databricks / Azure OpenAI

Toronto, Ontario, Canada | T4 Contract | Hybrid

End Client: Leading Global Insurance Organization

About the Role

Our consulting client is seeking a highly experienced AI Architect to lead the design and implementation of an enterprise-scale AI-powered Bordereaux (BDX) Processing Framework supporting Insurance MGA and Programs business operations.

The successful candidate will define and deliver a reusable, scalable framework leveraging Databricks Mosaic AI, Azure AI Services, Agentic AI, Azure OpenAI, Anthropic Claude, and Google Gemini to automate ingestion, mapping, standardization, validation, reconciliation, and onboarding of Bordereaux data from multiple MGA 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.

Responsibilities

AI & Framework Architecture

• Define enterprise architecture for AI-powered Bordereaux onboarding and processing

• Design reusable frameworks for BDX ingestion, AI-assisted mapping, data standardization, business-rule validation, data quality monitoring, and reconciliation workflows

• Establish architecture standards, design principles, and implementation patterns for future onboarding initiatives

Agentic AI Solution Design

• Design intelligent AI agents capable of understanding new Bordereaux layouts

• Map source columns to target canonical models

• Identify missing attributes and exceptions

• Recommend transformation rules and generate onboarding insights

• Architect Human-in-the-Loop approval workflows for business users

• Define multi-agent orchestration patterns across ingestion, mapping, validation, exception handling, and approval processes

Databricks & Azure Architecture

• Lead architecture using Databricks Mosaic AI, Databricks Vector Search, Delta Lake, Unity Catalog, MLflow, Lakeflow Pipelines, Azure OpenAI, and Azure Data Lake Storage

• Define Medallion Architecture and metadata-driven processing frameworks

• Architect scalable, cloud-native solutions supporting onboarding of multiple MGA partners and lines of business

Knowledge & Retrieval Architecture

• Design retrieval frameworks supporting data dictionaries, mapping repositories, business rules, historical onboarding knowledge, and transformation patterns

• Implement RAG-based solutions enabling 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

Required Skills / What You Bring

• 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

• Strong architecture experience with Azure OpenAI

• Experience with Anthropic Claude and Google Gemini

• Experience with Agentic AI frameworks including LangGraph, LangChain, AutoGen, CrewAI, and LlamaIndex

• Strong Databricks experience including Mosaic AI, Vector Search, Delta Lake, Unity Catalog, MLflow, Lakeflow Pipelines, and Databricks SQL

• Strong Azure experience including Azure AI Search, Azure Data Lake Storage, Azure Functions, Azure DevOps, and Azure Kubernetes Service

• Strong development and data engineering knowledge across Python, PySpark, SQL, Spark, and API Integrations

• Experience with Metadata-driven Framework Design, Data Quality, and Data Governance

Preferred Experience

• Bordereaux Processing (BDX)

• MGA & Programs Business

• Delegated Authority Business

• Policy & Claims Data Integration

• Underwriting Operations

• Insurance Data Modernization Programs