Knowledge Graph & Ontology Architect (GraphRAG)

Location: Nearshore – LATAM
Engagement: Full-time Contractor
Industry: Healthcare AI / Technology

About the Role

We are looking for a Knowledge Graph & Ontology Architect to design and own the knowledge representation layer behind an AI-powered healthcare platform.

You will be responsible for designing healthcare domain ontologies and knowledge graphs that enable AI agents to understand complex relationships, retrieve accurate information, and support real-world patient access workflows.

This role goes beyond working with graph databases. We are looking for someone with hands-on experience in ontology design, semantic modeling, knowledge representation, and production-scale GraphRAG systems.

You will work closely with AI, RAG, and engineering teams to transform complex, unstructured, and tenant-specific data into structured, connected knowledge that AI agents can reason over.

Responsibilities

Design and own healthcare domain ontologies, defining entities, relationships, attributes, and business rules.
Architect and implement multi-tenant knowledge graphs using Neo4j, FalkorDB, or similar graph databases.
Build and optimize GraphRAG solutions to improve information retrieval, reasoning, and LLM response accuracy.
Design data mapping strategies to transform complex source data, documents, and EHR information into standardized knowledge models.
Develop graph queries using Cypher and implement Text2Cypher patterns for AI agents and MCP tools.
Design schema versioning and evolution strategies to support changes without disrupting existing systems.
Establish data governance practices, including lineage, provenance, and ontology management.
Collaborate with AI/ML, RAG, and data engineering teams to integrate LLM-assisted extraction and knowledge graph capabilities.

Requirements

Strong experience designing and implementing Knowledge Graphs and domain ontologies.
Hands-on experience with semantic modeling, knowledge representation, and complex entity relationships.
Strong experience with Neo4j, FalkorDB, Redis, GraphDB, or equivalent graph technologies.
Proficiency in Cypher or equivalent graph query languages.
Experience building and deploying production-scale GraphRAG or RAG-based systems.
Strong Python programming skills and experience with data pipelines and ETL processes.
Understanding of multi-hop relationships, graph traversal, and reasoning layers.
Experience managing schema evolution and complex data models in production environments.
Ability to determine when to use graph databases versus relational or document-based databases.

Nice to Have

Healthcare data experience, particularly EHR, FHIR, HL7, or Clarity.
Experience with RDF, OWL, SPARQL, or formal ontology tools.
Experience implementing GraphRAG in production environments.
Background in taxonomy design or semantic modeling within regulated or complex industries.
Experience working with LLMs and AI-assisted entity extraction.

Why Join Us?

Work on advanced AI solutions transforming healthcare operations and patient access.
Take ownership of the knowledge architecture behind enterprise AI agents.
Collaborate with experienced engineering and AI teams.
Work remotely in a nearshore environment.
Opportunity to contribute to complex, production-level AI systems.

Knowledge Graph & Ontology (GraphRAG) A...