This role pays less than
75%
of similar roles. Most pay
$195,963–$288,037
— the shaded band above.
At the midpoint, this role pays about
$195k
versus about
$242k
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
61 open roles
on FindRole.
Listed pay typically runs
$127,600–$191,400
across 33 roles with salary data.
The Director Data and Analytics AI Engineering joins the Actuarial Solutions Engineering team to develop cloud-based data and analytics solutions for actuarial functions like pricing, underwriting, and portfolio management. This leader manages a technical team to deliver governed next-generation actuarial data products, semantic layers, and AI analytic agents. The role involves translating complex use cases into scalable Snowflake solutions while overseeing data discovery, modeling, transformation, and governance. Key responsibilities include building AI data pipelines for structured and unstructured data, managing the data lifecycle, and implementing RAG architectures. Required technical expertise includes LLMs, prompt engineering, vector stores like Pinecone or OpenSearch, and real-time data streaming. The candidate will navigate actuarial analytics to solve problems in loss ratio, rate adequacy, and renewal health while ensuring all products meet enterprise standards for quality and production readiness.
Lead the delivery of a complex portfolio of actuarial data products, semantic layers, and AI-enabled analytics.
Develop and implement a strategic roadmap to modernize legacy data systems using cloud and AI technologies.
Design and oversee Snowflake-based data pipelines that integrate structured and unstructured data for AI solutions.
Build and mentor a high-performing team of data engineers, analysts, and release train engineers.
Establish standardized processes for AI data engineering, including RAG architectures, vector stores, and automated quality frameworks.
Manage the budget, resources, and technical roadmap for the actuarial data and analytics portfolio.
Translate complex actuarial business requirements into scalable, production-ready data products and tools.
Evaluate emerging technologies to improve developer productivity and enhance enterprise data capabilities.
What we're looking for
8-10 years of experience in data engineering, analytics solution delivery, actuarial analytics, or related data-intensive roles.
3+ years of experience supporting actuarial, insurance, pricing, reserving, modeling, underwriting, portfolio management, or financial analytics use cases.
Mastery level skills in data engineering and architecture including data warehouses, integration, lakes, domains, products, business intelligence, and cloud technology.
Technical expertise in LLMs, AI platforms, prompt engineering, RAG architectures, and vector database technologies.
Experience enabling AI for analytics use cases such as analytic agents, natural language analytics, and governed knowledge bases.
Ability to design, implement, and oversee Snowflake-based data pipelines, transformations, validations, and analytic consumption patterns.
Proven experience building modern actuarial data products including governed consumption layers, semantic layers, and analytics-ready models.
Strong understanding of actuarial measures and analytical concepts such as loss ratio, frequency, severity, and rate adequacy (preferred).
AI
ML
LLMs
Python
Azure
Langchain
LangGraph
Data Architecture
Data Governance
Responsible AI
Model Risk Management
SLA Management
Continuous Improvement
Audit Readiness
Data Engineering
AWS
Azure
GCP
AI
ML
MLOps
Data Lakes
Metadata Management
Distributed Data Systems
Data Quality
Enterprise Architecture
Software Engineering
Digital Platforms
AI
ML
RAG
LLMs
Generative AI
Distributed Systems
Platform Engineering
Context Orchestration
Memory Systems
Retrieval Systems
Real-time Inference
Observability
System Optimization
Agent-based Systems