Translational AI Knowledge Architect & Graph Lead

6084-Janssen Research & Development, LLC Legal Entity; Spring House (PA); On-site; USD 117,000 - 201,250; Full time

Job summary

Johnson & Johnson seeks a Principal Translational Knowledge Architect & Graph Lead to design and implement semantic and knowledge architectures enabling AI-driven reasoning across discovery, safety, and clinical domains.

You will lead ontology development, governance, and knowledge graph infrastructure, partnering with scientists, data engineers, and platform teams to deliver AI-ready knowledge representations across translational pipelines.

Qualifications

• PhD or Master’s degree in Biomedical Informatics, Bioinformatics, Computational Biology, Computer Science, Information Science, Knowledge Engineering, or related field.
• 5+ years in biomedical informatics, semantic technologies, knowledge engineering, or scientific data architecture.
• Experience designing ontology-driven knowledge systems in life sciences, healthcare, or pharma R&D.

Responsibilities

• Design and maintain enterprise knowledge models spanning discovery biology, safety pharmacology, pathology, clinical development, real-world evidence.
• Develop semantic frameworks for translational reasoning across the R&D lifecycle and create AI-ready knowledge models.
• Lead ontology strategy, governance, and lifecycle management with provenance, traceability, and FAIR data principles.
• Design RDF-based knowledge graph architectures, mappings, inference rules, and reasoning frameworks for AI-enabled discovery.
• Harmonize data across SEND, SDTM, ADaM, MedDRA, HPO, MONDO, FHIR, OMOP, and related ontologies.

Skills

Ontology development

Knowledge modeling

RDF/OWL/SPARQL

Semantic Web technologies

Governance & FAIR data

Education

PhD in Biomedical Informatics

Master's degree in a related field

Tools

RDF

OWL

SHACL

SPARQL

Job description

Johnson & Johnson seeks a Principal Translational Knowledge Architect & Graph Lead to design and implement semantic and knowledge architectures enabling AI-driven reasoning across discovery, safety, and clinical domains.

You will lead ontology development, governance, and knowledge graph infrastructure, partnering with scientists, data engineers, and platform teams to deliver AI-ready knowledge representations across translational pipelines.