below marketmost similar roles pay hereabove market
This role pays more than
92%
of similar roles. Most pay
$146,987–$228,012
— the blue band above.
At the midpoint, this role pays about
$278k
versus about
$187k
for comparable roles.
Based on 240 similar postings.
Employer
About The Hartford
The Hartford is a leading provider of property and casualty insurance, group benefits, and mutual funds, serving businesses and individuals across the United States. Industry: Insurance & Financial Services
The Hartford currently has
74 open roles
on FindRole.
Listed pay typically runs
$127,600–$191,400
across 26 roles with salary data.
The VP AI Data Engineering leads the Business Insurance Data Engineering portfolio to shape the strategy, organization, and delivery of trusted, governed, and scalable data capabilities. This executive role involves translating business strategy into data products, modernization priorities, and AI-ready foundations. Key responsibilities include defining the operating model for agentic analytics, building enterprise data intelligence layers using ontologies and knowledge graphs, and establishing reusable semantic layers across underwriting, pricing, and claims. The role requires expertise in Python, SQL, Snowflake, Spark, Kafka, and cloud-native technologies like AWS or Google Cloud. The position focuses on solving complex data problems for Business Insurance by enabling generative AI, RAG, and agentic AI through robust pipelines, embeddings, vector technologies, and governed data contracts to ensure traceable evidence and measurable business outcomes.
Define and champion the Business Insurance AI Data Engineering strategy, operating model, and multi-year portfolio plans.
Set priorities and allocate resources for data products, modernization, AI-ready foundations, and technical debt.
Ensure delivery of scalable data products, pipelines, and semantic assets supporting generative AI and agentic AI.
Lead the agentic analytics strategy to enable governed AI agents that reason over and act on enterprise data.
Build enterprise data intelligence layers combining business semantics, ontologies, knowledge graphs, and access controls.
Establish reusable semantic layers and governed business metrics across all core insurance business functions.
Define operating models and controls for agentic data, including identity, authorization, observability, and audit trails.
Lead a large technical organization by strengthening leadership effectiveness, talent development, and organizational health.
What we're looking for
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, Applied Mathematics, Business, or a related field (advanced degree preferred).
18+ years of applicable experience in Data Engineering, data platforms, AI-ready data ecosystems, software engineering for data-intensive systems, or technology leadership.
10+ years of progressive leadership experience leading senior leaders, large technical organizations, or complex portfolios.
Significant Property & Casualty or Business Insurance experience (preferred).
Mastery of modern Data Engineering and AI-ready data foundations, including data products, pipelines, data contracts, and semantic/contextual data.
Deep expertise in enterprise data intelligence patterns, including semantic layers, ontologies, knowledge graphs, and governed metrics.
Strong fluency in Python, SQL, distributed processing, Snowflake, Spark, Kafka, and cloud-native technologies (AWS or Google Cloud).
Applied AI
Generative AI
Agentic AI
Machine Learning
Data Science
Predictive Analytics
Model Risk Management
AI Governance
Feature Engineering
Quantitative Methods
Forecasting
Data Modeling
Production AI Operations
Responsible AI
Automation
Generative AI
Machine Learning
SQL
RAG
LLM
Data Modeling
Data Integration
APIs
Data Visualization
Predictive Analytics
Automation
Data Lineage
Metrics Definition
Data Transformation