Principal Ontologist, Graph Modeler

This is a fully remote position, open to applicants in Connecticut, +1 more state.

📋 Description

• Oversee the design and implementation of enterprise-scale semantic layers for the Business Insurance data portfolio to standardize business definitions and facilitate reliable analytics, AI, and agentic applications.

• Establish and operationalize ontologies, context graphs, and knowledge graphs across Business Insurance domains to enhance reasoning, explainability, and decision intelligence.

• Model essential insurance concepts and relationships involving customers, accounts, submissions, quotes, policies, coverages, products, risks, claims, producers, and portfolio performance.

• Support semantic-first AI and agentic analytics by ensuring that large language models and agents can access governed business context, metrics, rules, and relationships.

• Create canonical semantic vocabularies that unify meanings across both structured and unstructured Business Insurance data sources.

• Lead production-scale execution of semantic and graph platforms, establishing standards for performance, governance, security, and lifecycle management.

• Define and advocate for standards and reusable patterns for ontology modeling, graph modeling, semantic interoperability, and ontology reuse across delivery teams.

• Collaborate with Business Insurance data product owners, domain leaders, architects, and engineers to integrate semantic models into data products, AI pipelines, analytics, and activation layers.

• Work closely with AI Data Architects and AI Data Engineers to operationalize ontologies through graphs, metadata services, APIs, and production data platforms.

• Align ontologies and graph models with enterprise data governance, metadata, lineage, quality, privacy, and security standards.

• Facilitate explainability by ensuring AI and analytical outputs can be traced back to governed semantic definitions, relationships, rules, and source data.

• Act as the primary authority on semantic engineering, ontology, and graph-modeling practices that support the Business Insurance data portfolio.

• Enhance agentic data engineering through reference patterns, playbooks, proofs of value, and production implementations.

• Contribute to communities of practice, reference guidance, reusable assets, and internal enablement resources.

⛳️ Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Information Management, or a related field, or equivalent professional experience with large-scale data warehouse systems.

• 8–12+ years of direct experience in semantic layer architecture, ontology modeling, graph modeling, and knowledge graph design at an enterprise level.

• Profound, hands-on expertise with RDF, OWL (OWL 2), RDFS, SKOS, SPARQL, and W3C semantic web standards.

• Demonstrated experience in designing and managing enterprise knowledge graphs and governed semantic assets.

• Practical experience with graph or triple-store technologies such as Neo4j, Amazon Neptune, or Spanner Graph.

• Experience integrating knowledge graphs with large language models, retrieval-augmented generation pipelines, vector stores, and agentic frameworks.

• Strong understanding of AI consumption patterns, including embeddings, grounding, reasoning, and explainability.

• Experience in merging semantic layers with data platforms, APIs, metadata systems, analytics platforms, and AI pipelines.

• Capability to convert complex insurance domain knowledge into formal, machine-readable semantic and graph structures.

• Strong grasp of context-aware data engineering, canonical modeling, and semantic interoperability.

• Proven track record of transitioning from strategy to pilot projects and scaling enterprise capabilities.

• Strong executive influence and thought leadership in semantic engineering, agentic analytics, and AI-native data engineering.

• Practical experience with AWS, GCP, and Snowflake.

• Knowledge of the Business Insurance domain across various areas such as underwriting, policy, claims, distribution, product, customer, or portfolio management.

• Exceptional communication, presentation, collaboration, and technical leadership abilities.

• Candidate must have authorization to work in the US without company sponsorship.

• The organization will not provide support for the STEM OPT I-983 Training Plan endorsement for this position.

🏝️ Benefits

• Short-term or annual bonuses

• Long-term incentives

• On-the-spot recognition

• Perks & Benefits