Principal Data and AI Architect

MSIG USA•Warren Township, NJ

1d•Hybrid

About The Position

MSIG USA is seeking a seasoned Enterprise Data & AI Architect at the Lead/Principal level to serve as the technical authority and strategic design leader for MSIG USA's enterprise data platform and AI ecosystem. This is one of the most impactful and senior individual contributor roles within our Data, Analytics & AI organization. You will be responsible for defining the overarching architecture across our data platforms, AI/ML systems, data governance frameworks, and integration patterns — ensuring they are cohesive, scalable, secure, and aligned with our P&C insurance business strategy. You will set the technical direction, establish engineering standards, guide platform decisions, and serve as a trusted advisor to the CDAO, technology leadership, and business domain leaders across Underwriting, Claims, Actuarial, Finance, and Reinsurance. This is a role for a deeply technical, intellectually curious architect who is equally comfortable shaping long-term strategies and rolling up their sleeves to validate designs, prototype solutions, and guide engineering teams through complex delivery challenges.

Requirements

Bachelor’s degree in computer science, Information Systems, Data Engineering, or a related technical field.
8–12 years of progressive experience in data architecture, data engineering, or enterprise architecture roles — with at least 5 years in a senior or lead architect capacity.
Demonstrated experience designing and delivering enterprise-scale data platforms in cloud environments, with a strong preference for Microsoft Azure and Databricks.
Proven track record of architecting production AI/ML systems including MLOps pipelines, LLM-powered applications, and agentic frameworks.
Significant experience in financial services, insurance, or similarly regulated industries — P&C insurance domain experience strongly preferred.
Experience working directly with C-suite and senior business leaders as a technical advisor and architecture authority.

Nice To Haves

Master's degree strongly preferred.

Responsibilities

Define and own the enterprise data and AI architecture blueprint for MSIG USA, covering data ingestion, storage, transformation, serving, governance, and AI/ML deployment.
Establish the target state architecture across cloud platforms, data products, AI systems, and integration patterns — with a clear, pragmatic roadmap from current to future state.
Lead architecture governance — chairing design reviews, evaluating technology proposals, and enforcing standards across data engineering, AI/ML, and analytics teams.
Translate MSIG USA's business strategy and regulatory obligations into concrete, actionable architectural decisions with well-documented tradeoffs.
Serve as the primary technical liaison between the CDAO, IT leadership, and enterprise architecture functions across MS&AD Insurance Group.
Architect and evolve MSIG USA's hybrid data platform built on Microsoft Fabric, Databricks, and Azure Data Lake (OneLake) — ensuring the platform supports batch, streaming, and real-time data workloads across all insurance domains.
Design the Medallion (Bronze/Silver/Gold) architecture and enforce lakehouse best practices including Delta Lake, Unity Catalog, and data product publishing patterns aligned to Data Mesh principles.
Define data modeling standards across entity types — Policy, Customer/Party, Claims, Exposure, Premium, Loss, and Reinsurance — ensuring consistency across the enterprise.
Oversee the architecture of the Master Data Management (MDM) platform (Profisee) and its integration with upstream policy systems, downstream analytics, and the data lakehouse.
Design enterprise data integration patterns — API-first, event-driven, and ETL/ELT architectures — connecting policy administration systems, claims platforms, financial systems, and external data providers to the central data platform.
Ensure platform architecture meets high availability, disaster recovery, scalability, and cost efficiency requirements for a regulated insurance environment.
Define the enterprise AI/ML architecture — spanning model development, training, deployment, monitoring, and governance — built on Databricks Mosaic AI, Azure Machine Learning, and Azure OpenAI.
Architect the MLOps platform including CI/CD pipelines for ML models, feature store design, model registry, experiment tracking (MLflow), and production model serving.
Design Generative AI and LLM architectures — including Retrieval-Augmented Generation (RAG) systems, agentic frameworks, prompt management, and responsible AI guardrails — for insurance use cases across underwriting, claims, and actuarial functions.
Establish AI governance and model risk management frameworks ensuring all production AI systems are explainable, auditable, and compliant with regulatory expectations.
Evaluate and recommend foundational models, AI platforms, and emerging technologies — maintaining an architectural view of the evolving AI landscape and its applicability to P&C insurance.
Design the enterprise data governance architecture in partnership with the Data Governance function — covering data cataloging, lineage, classification, quality, and stewardship workflows using Microsoft Purview.
Define data access control and security architecture — including role-based access control (RBAC), column/row-level security, data masking, and encryption standards across all platform layers.
Ensure architecture adherence to regulatory and compliance requirements including NAIC, SOC 2, CCPA, and GDPR as applicable to insurance data.
Architect data lineage and audit trails to support actuarial certification, financial audit readiness, and regulatory examination requirements.
Define and maintain the enterprise data and AI engineering standards — including coding standards, design patterns, testing frameworks, CI/CD practices, and documentation requirements.
Create and curate a reference architecture library of reusable patterns for ingestion, transformation, serving, AI deployment, and integration — reducing duplication and accelerating delivery across domain teams.
Conduct architecture reviews and design critiques for major initiatives, providing structured guidance that balances technical rigor with delivery pragmatism.
Mentor and coach senior data engineers, ML engineers, and domain architects — elevating the overall technical quality and architectural thinking across the team.
Stay current with the evolving data and AI technology landscape and bring forward well-reasoned recommendations for platform evolution.
Partner with Underwriting, Claims, Actuarial, Finance, and Reinsurance business leaders to understand domain data needs and translate them into durable architectural solutions.
Collaborate with IT, Enterprise Architecture, Information Security, and Vendor Management to ensure data and AI architecture is aligned with enterprise technology standards and procurement strategy.
Represent data and AI architecture in vendor evaluations, RFPs, and technology due diligence — providing structured assessments of platform capabilities, integration complexity, and total cost of ownership.
Produce executive-ready architecture documentation, roadmaps, and position papers for CDAO and senior leadership consumption.