Director, Knowledge Graph & Semantics - HYBRID ROLE
Vertex Pharmaceuticals
August 10, 2026
Remote friendly (Boston, MA)
United States
IT
Key Duties and Responsibilities
- Design, build, and operate Vertex’s enterprise knowledge graph spanning clinical, research, regulatory, and commercial domains (ingestion, storage, query, lifecycle management of nodes/edges/properties).
- Build and govern the enterprise semantic layer enabling metrics, dimensions, business entities, and relationships in a single consistent model for AI agents.
- Define graph and semantic strategy, including technology selection (graph database, AI semantic layer tooling, query API) and unified architecture.
- Partner on ontology/data modeling to translate domain ontologies into the graph with fidelity to source models.
- Build graph traversal and retrieval interfaces for AI agents/consumers (pattern queries, semantic search, graph-aware retrieval for RAG).
- Onboard applications and systems into the knowledge graph and semantic layer.
- Own production operations (SLAs, observability, query performance, cost, continuous improvement).
Knowledge and Skills (Required)
- 10+ years in data engineering, AI/ML, or advanced analytics; 3+ years focused on knowledge graphs/semantic technologies/enterprise data modeling at scale.
- Deep hands-on knowledge graph experience (schema, ingestion, query, traversal; property/RDF/hybrid + vector paradigms).
- Strong semantic layer expertise (dbt Semantic Layer, Cube, AtScale, LookML, or comparable).
- Strong Snowflake and/or Databricks experience.
- Proven cross-domain integration (entity resolution, master data, lineage).
- Understanding of AI-agent and RAG consumption (graph-aware retrieval/traversal).
- Track record of production operations.
- Leadership and communication with executives; translate business needs into models.
Preferred
- Pharma/life sciences context.
- Regulated environment knowledge (GxP, 21 CFR Part 11, validated systems).
- Life sciences ontologies (SNOMED CT, MedDRA, LOINC, RxNorm, CDISC, IDMP).
- Graph query languages (Cypher, SPARQL, Gremlin, GQL, etc.).
- LLM integration for graph query generation (text-to-Cypher/SPARQL) and graph-augmented retrieval.
Pay Range
- $216,400 - $324,600
Application Instructions
- Contact Talent Acquisition at ApplicationAssistance@vrtx.com for accommodation requests related to the hiring process or performing essential functions.
- Design, build, and operate Vertex’s enterprise knowledge graph spanning clinical, research, regulatory, and commercial domains (ingestion, storage, query, lifecycle management of nodes/edges/properties).
- Build and govern the enterprise semantic layer enabling metrics, dimensions, business entities, and relationships in a single consistent model for AI agents.
- Define graph and semantic strategy, including technology selection (graph database, AI semantic layer tooling, query API) and unified architecture.
- Partner on ontology/data modeling to translate domain ontologies into the graph with fidelity to source models.
- Build graph traversal and retrieval interfaces for AI agents/consumers (pattern queries, semantic search, graph-aware retrieval for RAG).
- Onboard applications and systems into the knowledge graph and semantic layer.
- Own production operations (SLAs, observability, query performance, cost, continuous improvement).
Knowledge and Skills (Required)
- 10+ years in data engineering, AI/ML, or advanced analytics; 3+ years focused on knowledge graphs/semantic technologies/enterprise data modeling at scale.
- Deep hands-on knowledge graph experience (schema, ingestion, query, traversal; property/RDF/hybrid + vector paradigms).
- Strong semantic layer expertise (dbt Semantic Layer, Cube, AtScale, LookML, or comparable).
- Strong Snowflake and/or Databricks experience.
- Proven cross-domain integration (entity resolution, master data, lineage).
- Understanding of AI-agent and RAG consumption (graph-aware retrieval/traversal).
- Track record of production operations.
- Leadership and communication with executives; translate business needs into models.
Preferred
- Pharma/life sciences context.
- Regulated environment knowledge (GxP, 21 CFR Part 11, validated systems).
- Life sciences ontologies (SNOMED CT, MedDRA, LOINC, RxNorm, CDISC, IDMP).
- Graph query languages (Cypher, SPARQL, Gremlin, GQL, etc.).
- LLM integration for graph query generation (text-to-Cypher/SPARQL) and graph-augmented retrieval.
Pay Range
- $216,400 - $324,600
Application Instructions
- Contact Talent Acquisition at ApplicationAssistance@vrtx.com for accommodation requests related to the hiring process or performing essential functions.