Head of Knowledge Graph & AI Ontology

Bain & Company; Boston (MA); On-site; USD 210,000 - 280,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Paid time off

401(k) with company matching

Parental leave

Job summary

Bain & Company in Boston, MA is seeking a Head of Ontology to lead knowledge engineering across Growth AI Performance System. You will own the knowledge graph, taxonomy, and data pipelines, partnering with AI engineers, data scientists, and senior client stakeholders.

This role blends data engineering and AI, requiring native fluency in retrieval, embeddings, and RAG architectures. You’ll shape architecture, ensure governance, and drive commercial outcomes with scalable ontology.

Qualifications

• Strong hands-on engineering for data and AI, including production pipelines.
• Deep knowledge of ontology design, knowledge graphs, and taxonomy governance.
• Experience with entity resolution, retrieval, and embedding architectures.
• Proficiency with NLP/ML tools for taxonomy enrichment from unstructured data.
• Ability to lead a small team and engage with senior client stakeholders.

Responsibilities

• Own design, build, and governance of the knowledge graph and ontology.
• Define architecture standards for entity naming, taxonomy, and relationships.
• Design and implement scalable entity resolution systems.
• Develop and evolve graph/semantic stores (Neo4j, Neptune, RDF/OWL).
• Lead the Ontology and Knowledge team and collaborate with Tech Lead and Data Scientists.

Skills

Data engineering

AI engineering

Ontology design

Knowledge graph

NLP/ML

RAG architecture

Spark/PySpark

Airflow

dbt

Embedding pipelines

Retrieval systems

Education

Bachelor’s degree or higher in CS/IT/Data engineering

Tools

Splink

Zingg

Neo4j

Neptune

RDF/OWL

SPARQL

Pinecone

Weaviate

LangGraph

MCP

Job description

Bain & Company in Boston, MA is seeking a Head of Ontology to lead knowledge engineering across Growth AI Performance System. You will own the knowledge graph, taxonomy, and data pipelines, partnering with AI engineers, data scientists, and senior client stakeholders.

This role blends data engineering and AI, requiring native fluency in retrieval, embeddings, and RAG architectures. You’ll shape architecture, ensure governance, and drive commercial outcomes with scalable ontology.