Chief AI Data Engineering & Strategy

Hartford; Hartford (CT); Hybrid; USD 222,000 - 334,000; Full time

Job summary

The Hartford is seeking a visionary Vice President of AI Data Engineering to shape data foundations for Business Insurance. This senior leader will translate business priorities into scalable data products, AI-ready pipelines, and governance across underwriting, pricing, servicing, and claims.

Based in Hartford, CT or the NYC/NJ metro area with a hybrid work model, you will lead a large organization, drive modernization, and partner with AI, Analytics, Architecture, and Product to deliver

Qualifications

• 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, technology leadership, or related disciplines.
• 10+ years of progressive leadership experience, including leading senior leaders, large technical organizations, complex portfolios, or business‑critical enterprise capabilities.
• Demonstrated success translating business strategy into Data Engineering strategy, operating models, portfolio priorities, resource plans, workforce capabilities, and multi‑year roadmaps.
• Proven experience establishing enterprise data‑product, semantic‑layer, or data‑intelligence capabilities that improve trusted reuse, consistent business interpretation, and measurable outcomes.
• Demonstrated leadership in enabling advanced analytics, generative AI, RAG, or agentic analytics through governed, context‑rich, and traceable enterprise data foundations.
• Experience partnering across Data Engineering, Analytics, AI, Architecture, Product, Governance, Risk, and business teams to deliver shared capabilities and resolve complex ownership and operating‑model decisions.
• Proven experience managing significant budgets, workforce resources, strategic vendors, modernization priorities, and portfolio performance.
• Strong business and financial acumen with the ability to connect Data and AI capabilities to measurable Business Insurance outcomes.
• Meaningful experience advising executive leaders, influencing strategic decisions, navigating complex tradeoffs, and leading organizational change, including adoption of AI‑enabled ways of working.
• Exceptional executive communication, judgment, negotiation, relationship management, conflict resolution, presentation, and storytelling skills.
• Significant Property & Casualty or Business Insurance experience strongly preferred.

Responsibilities

• Define and champion the Business Insurance AI Data Engineering strategy and operating model, translating business priorities into multi-year portfolio plans, capability roadmaps, workforce requirements, and measurable outcomes.
• Set priorities and allocate resources across data products, modernization, AI-ready data foundations, technical debt, operational resilience, and emerging business needs.
• Ensure delivery and ongoing operation of trusted, reusable, and scalable data products, pipelines, semantic assets, and data foundations supporting analytics, automation, machine learning, generative AI, RAG, and agentic AI.
• Lead the Business Insurance agentic analytics strategy, enabling governed AI agents and decision-support experiences that can discover, interpret, reason over, and act on trusted enterprise data while maintaining human accountability for material business decisions.
• Build and scale enterprise data intelligence layers that combine business semantics, contextual metadata, ontologies, knowledge graphs, metrics, policies, lineage, and access controls so analytics and AI consistently interpret Business Insurance data in the right business context.
• Establish reusable semantic layers and governed business metrics across underwriting, pricing, distribution, servicing, claims, risk, customer, operations, and finance, reducing inconsistent definitions and accelerating trusted self-service and AI-assisted analysis.
• Partner with Analytics, AI, Architecture, Product, Governance, and business leaders to deliver context-rich data products and retrieval patterns that ground generative and agentic AI in authoritative data, approved definitions, and traceable evidence.
• Define the operating model and controls for agentic data and analytics, including agent access, identity, authorization, observability, evaluation, audit trails, feedback loops, exception handling, and lifecycle management.
• Connect Data Engineering capabilities to outcomes across underwriting, pricing, distribution, servicing, claims, risk management, customer, operational, and financial priorities.
• Guide the evolution of structured and unstructured data capabilities, including metadata, semantic assets, contextual data, embeddings, vector and graph technologies, retrieval and grounding data, and governed external data sources.
• Establish expectations for data quality, testing, lineage, traceability, observability, reliability, lifecycle management, operational readiness, data contracts, service levels, and consumer accountability.
• Champion responsible use of AI-assisted engineering to improve productivity, quality, testing, documentation, and delivery speed while maintaining appropriate human oversight and controls.
• Lead a large, complex organization through senior leaders, strengthening leadership effectiveness, organizational health, succession, talent development, and long‑term capability sustainability.
• Own portfolio delivery, operational performance, cost effectiveness, workforce outcomes, risk management, control maturity, audit readiness, and value realization.
• Partner with business and technical executives to align priorities, architecture direction, platform capabilities, governance requirements, dependencies, and outcomes while maintaining clear Data Engineering accountability.
• Remove organizational and cross‑functional barriers, guide major multidimensional initiatives, and adjust priorities based on business, financial, workforce, operational quality, and risk insights.
• Represent Business Insurance AI Data Engineering with senior leaders, governance bodies, strategic partners, and vendors while monitoring emerging data and AI trends and their business implications.

Skills

Data strategy

Executive leadership

Business and data alignment

Communication

Change management

Education

Bachelor's degree in Computer Science or related field

Advanced degree preferred

Tools

Python

SQL

Snowflake

Spark

Kafka

Job description

The Hartford is seeking a visionary Vice President of AI Data Engineering to shape data foundations for Business Insurance. This senior leader will translate business priorities into scalable data products, AI-ready pipelines, and governance across underwriting, pricing, servicing, and claims.

Based in Hartford, CT or the NYC/NJ metro area with a hybrid work model, you will lead a large organization, drive modernization, and partner with AI, Analytics, Architecture, and Product to deliver