Director, Knowledge Graph & Semantics (AI)

Location: Boston, MA; hybrid work requires three days per week in the Boston office, or five days per week on-site.

Salary: $216,400–$324,600 annual base salary, plus eligible bonus and equity awards.

Company

Vertex is a global biotechnology company focused on scientific innovation and developing better outcomes for patients.

What you will do

• Lead the Knowledge Graph & Semantics function within the Data Engineering organization.
• Design, build, and operate an enterprise knowledge graph spanning clinical, research, regulatory, and commercial domains.
• Build and govern a semantic layer for business entities, metrics, dimensions, and relationships used by AI agents and analytical systems.
• Define the graph and semantic platform strategy, including technology selection, architecture, query APIs, and graph databases.
• Develop traversal, semantic search, and graph-aware retrieval interfaces for AI agents and RAG systems.
• Own system onboarding, SLAs, observability, query performance, cost, and continuous production improvement.

Requirements

• 10+ years of experience in data engineering, AI/ML, or advanced analytics, including 3+ years focused on knowledge graphs, semantic technologies, or enterprise data modeling at scale.
• Hands-on expertise designing and operating enterprise knowledge graphs, including schema design, ingestion, querying, traversal, and lifecycle management.
• Experience building semantic layers with technologies such as dbt Semantic Layer, Cube, AtScale, LookML, or comparable platforms.
• Strong enterprise experience with Snowflake and/or Databricks, cross-domain data integration, entity resolution, master data, and lineage.
• Ability to lead technical teams, communicate with executives, and translate business needs into graph and semantic models.
• Ability to work in the Boston office at least three days per week for the hybrid arrangement.

Nice to have

• Pharmaceutical, biotechnology, or life sciences data experience.
• Experience with GxP, 21 CFR Part 11, validated systems, and life sciences ontologies such as SNOMED CT, MedDRA, LOINC, RxNorm, CDISC, or IDMP.
• Experience with Cypher, SPARQL, Gremlin, GQL, or comparable graph query languages.
• Experience with text-to-Cypher, text-to-SPARQL, or graph-augmented retrieval for AI systems.

Culture & Benefits

• Continuous learning and support for staying current with AI, technology, automation, and industry trends.
• Medical, dental, and vision coverage with resources supporting financial, family, and personal wellbeing.
• Generous paid time off, including summer and winter company shutdowns.
• Educational assistance, student loan repayment support, commuting subsidy, charitable donation matching, and 401(k).
• Equal employment opportunity and reasonable accommodation support.