VP AI Data Engineering, Business Insurance (AI)

Location: Hybrid; based in Hartford, CT or the NYC/NJ metro area. Must be eligible to work in the US without company sponsorship.

Company

hirify.global is an insurance company advancing data and AI capabilities across Business Insurance.

What you will do

• Define and champion the Business Insurance AI Data Engineering strategy, operating model, portfolio plans, capability roadmaps, workforce requirements, and measurable outcomes.
• Lead delivery and operation of trusted, reusable, scalable data products, pipelines, semantic assets, and AI-ready data foundations for analytics, automation, machine learning, generative AI, RAG, and agentic AI.
• Build enterprise data intelligence capabilities using semantic layers, contextual metadata, ontologies, knowledge graphs, governed metrics, lineage, policies, and access controls.
• Establish operating controls for agentic data and analytics, including identity, authorization, observability, evaluation, audit trails, exception handling, and lifecycle management.
• Connect Data Engineering capabilities to underwriting, pricing, distribution, servicing, claims, risk, customer, operations, and finance outcomes.
• Lead a large organization through senior leaders while owning portfolio delivery, operational performance, budgets, workforce outcomes, risk management, audit readiness, and value realization.

Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Engineering, Applied Mathematics, Business, or a related field; an advanced degree is 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, including 10+ years of progressive leadership experience.
• Experience translating business strategy into Data Engineering strategy, operating models, portfolio priorities, resource plans, workforce capabilities, and multi-year roadmaps.
• Experience establishing enterprise data-product, semantic-layer, or data-intelligence capabilities and enabling advanced analytics, generative AI, RAG, or agentic analytics through governed, traceable data foundations.
• Experience partnering across Data Engineering, Analytics, AI, Architecture, Product, Governance, Risk, and business teams, and managing significant budgets, workforce resources, strategic vendors, modernization priorities, and portfolio performance.
• Strong business and financial acumen, executive communication, judgment, negotiation, relationship management, conflict resolution, presentation, and storytelling skills.
• Mastery of modern Data Engineering and AI-ready data foundations, including data products, pipelines, data contracts, semantic and contextual data, metadata, lineage, quality, observability, reliability, testing, and lifecycle management.
• Deep expertise in enterprise data intelligence, semantic layers, governed metrics, business glossaries, ontologies, knowledge graphs, policies, lineage, access controls, agentic analytics, retrieval and grounding, human-in-the-loop controls, evaluation, observability, auditability, and lifecycle governance.
• Strong fluency in Python, SQL, distributed processing, Snowflake, Spark, Kafka, cloud-native technologies, orchestration, streaming, APIs, AWS or Google Cloud, and hybrid or multi-cloud environments.
• Deep understanding of Data Governance, Responsible AI, privacy, security, model and data risk, regulatory obligations, compliance, records management, and enterprise control frameworks.

Nice to have

• Significant Property & Casualty or Business Insurance experience.
• Advanced degree.

Culture & Benefits

• Full-time employment with a hybrid work arrangement.
• Total compensation may include base pay, short-term or annual bonuses, long-term incentives, and on-the-spot recognition.
• Work includes responsible adoption of AI-assisted engineering with human oversight and appropriate governance controls.