[Hiring] Knowledge Graph & Semantic Architect @American IT Systems

Role Description

The Knowledge Graph & Semantic Architect is responsible for designing and implementing enterprise semantic models, healthcare knowledge graphs, and AI-ready data ecosystems on Google Cloud Platform (GCP). This role enables semantic interoperability, healthcare data discovery, advanced analytics, GenAI, and clinical intelligence by integrating healthcare data, ontologies, metadata, and industry standards across the enterprise.

Key Responsibilities

• Define and execute the enterprise semantic architecture and knowledge graph strategy.
• Design and implement healthcare knowledge graphs representing patients, providers, encounters, diagnoses, medications, and clinical outcomes.
• Develop and govern healthcare ontologies, taxonomies, semantic models, and business vocabularies.
• Enable semantic interoperability leveraging FHIR, HL7, C-CDA, X12, DICOM, OMOP, and OpenEHR.
• Integrate semantic solutions with metadata catalogs, business glossaries, data lineage, and master data management platforms.
• Design semantic layers and graph-based solutions supporting GenAI, RAG, clinical decision support, population health, and healthcare analytics.
• Implement semantic search, knowledge discovery, and natural language data exploration capabilities.
• Establish governance standards for knowledge graphs, ontologies, semantic models, and AI data assets.
• Partner with Data Governance, Data Engineering, Analytics, AI, and Clinical Informatics teams to drive enterprise adoption.

Qualifications

• 10+ years of Data Architecture, Information Architecture, or Semantic Technology experience.
• 5+ years designing enterprise knowledge graph, ontology, or semantic solutions.
• Experience supporting enterprise AI, analytics, interoperability, and data governance initiatives.

Technical Skills

• Semantic & Knowledge Graph
• Knowledge Graph Architecture
• RDF, OWL, SKOS, Linked Data
• Ontology & Taxonomy Development
• SPARQL, Cypher
• Semantic Modeling & Knowledge Engineering
• Google Cloud Platform (GCP) Tech Stack
• AI & Analytics
• Generative AI
• Retrieval-Augmented Generation (RAG)
• Machine Learning
• NLP
• Semantic Search
• Knowledge Engineering

Preferred Technologies

• Neo4j
• Stardog
• GraphDB
• Collibra