AVP, AI Data Engineering, Customer Data Ecosystem

The Hartford

AVP of AI Data Engineering leading data architecture for Customer Data Ecosystem within an insurance company. Responsible for defining scalable AI-ready data architecture and leading a high-performance team.

Posted 5/27/2026full-timeHartford • Connecticut, Illinois, Ohio • 🇺🇸 United StatesLead💰 $182,000 - $273,000 per yearWebsite

About the role

Key responsibilities & impact

Lead the strategy and execution of complex and large Data and Analytics portfolio.
Ensure data architecture and solutions align with enterprise-wide standards for Data, AI and Analytics.
Effectively communicate strategy, execution progress, and outcomes to diverse stakeholders and promote data capabilities through thought leadership and presentations.
Responsible for implementing AI data pipelines that integrate structured, semi-structured, and unstructured data to support AI and Agentic solutions.
Design, build and maintain scalable real-time data pipelines for efficient ingestion, processing, and delivery.
Define and operationalize ontologies, context graphs, and knowledge graphs across domains to power reasoning, explainability, and decision intelligence.
Ensure semantic-first AI and Agentic analytics, ensuring LLMs and agents can consume governed business context, metrics, and rules.
Drive production-scale execution of semantic and knowledge platforms with strong standards for performance, governance, security, and lifecycle management.
Identify and champion AI augmented productivity improvements across the end-to-end data management lifecycle.
Stay current with emerging trends in Agentic AI and data engineering and lead proof-of-concepts and early pilots for emerging data and AI augmented technologies to accelerate speed to market.
Define and implement robust data management frameworks to ensure successful adoption of Enterprise Data Governance and Data Quality practices.
Effectively manage the budget and financials for the portfolio.

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Data Science or a related field
12+ years in data engineering, data management and building large-scale data ecosystems
7+ years in senior leadership roles managing complex data and AI portfolio with hands-on experience
Expertise in real-time data streaming, agentic frameworks, Data APIs, vector stores, and RAG architecture, self-serve analytics and AI
Deep expertise in semantic layer architecture, ontology modeling, and knowledge graph design at enterprise scale
Experience integrating knowledge graphs with LLMs, RAG pipelines, vector stores, and Agentic frameworks
Strong understanding of context-aware data engineering and semantic interoperability
Proven ability to move from strategy → pilot → scaled enterprise capability.
Strong executive influence and thought leadership in Agentic analytics and AI native data engineering.

Benefits

Comp & perks

Health insurance
Bonuses
Flexible work arrangements
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data architectureAI data pipelinesreal-time data streamingagentic frameworksData APIsvector storesRAG architecturesemantic layer architectureontology modelingknowledge graph design

Soft Skills

communicationthought leadershipexecutive influencestrategic thinkingstakeholder managementbudget managementteam leadershipdecision intelligencecollaborationadaptability

Certifications

Bachelor’s degree in Computer ScienceMaster’s degree in Data Science