Director, Knowledge Graph & Semantics (Biotech)

TL;DR

Director, Knowledge Graph & Semantics (Biotech): Leading the enterprise knowledge graph and semantic layer strategy to unify clinical, research, and commercial data for AI-driven decision-making. Focus on building scalable graph architectures, enabling AI agent reasoning through RAG systems, and governing semantic models across complex pharmaceutical domains.

Location: Must be based in the US. This role offers flexible work arrangements including remote, hybrid (3 days/week in Boston office), or on-site options.

Company

hirify.global is a global biotechnology company dedicated to scientific innovation and developing transformative medicines.

What you will do

• Define and execute the enterprise strategy for knowledge graph and semantic platform technologies.
• Design and operate a unified knowledge graph spanning clinical, research, regulatory, and commercial domains.
• Build and govern a semantic layer to ensure consistent metrics and business entities for AI and analytical consumers.
• Develop graph traversal and retrieval interfaces to support AI agents and RAG systems.
• Partner with ontology and data modeling teams to ensure high-fidelity data integration.
• Own production operations, including SLAs, query performance, and observability for graph systems.

Requirements

• Must be based in the United States.
• 10+ years of experience in data engineering, AI/ML, or advanced analytics.
• 3+ years of hands-on experience specifically with knowledge graphs, semantic technologies, or enterprise data modeling.
• Strong experience with cloud data platforms like Snowflake or Databricks.
• Proven ability to lead technical teams and communicate complex strategies to executive stakeholders.
• Experience building and governing semantic layers such as dbt Semantic Layer, Cube, or AtScale.

Nice to have

• Experience in pharmaceutical, biotech, or life sciences data environments.
• Knowledge of GxP, 21 CFR Part 11, and validated-system constraints.
• Familiarity with industry ontologies like SNOMED CT, MedDRA, or CDISC.
• Experience with graph query languages (Cypher, SPARQL, Gremlin, GQL).
• Experience with LLM-driven graph query generation and graph-augmented retrieval.

Culture & Benefits

• Comprehensive medical, dental, and vision benefits.
• Generous paid time off, including company-wide summer and winter shutdowns.
• Educational assistance programs including student loan repayment.
• 401(k) retirement plan with company matching.
• Commuting subsidy and flexible work environment.