AI Knowledge Graph & Ontology Manager

Accenture PLC; St. Louis (MO); On-site; USD 150,000 - 210,000; Full time

Job summary

Accenture is seeking an engineer to lead ontology work on knowledge-graph design and retrieval-augmented generation. You will drive schema and taxonomy design, construct the knowledge graph, and engineer agent context for efficient consumption of knowledge.

Travel up to 100% may be required depending on client needs. We value 5+ years in AI/LLM-related knowledge engineering, strong graph tech (RDF, SPARQL, graph DBs), and experience leading teams in agile contexts.

Qualifications

• Minimum 5 years in knowledge engineering, semantic web, ontology design, or taxonomy/data modeling with 1–2 years AI/LLM work.
• Minimum 3 years with knowledge graph tech (RDF, SPARQL, property graphs, SHACL) and graph DBs.
• AI-adjacent credentials with 1–2 years LLM work in production/near production contexts.
• Minimum 1 year experience with retrieval-augmented generation and agent context engineering.
• Minimum 2 years leading a team or workstream in a larger program.
• Minimum 5 years experience in agile engineering or consulting teams.
• Bachelor’s degree or equivalent (12 years) work experience; Associate’s degree requires 6+ years work experience.

Responsibilities

• Lead ontology work on a single engagement: schema and taxonomy design, knowledge-graph construction, and retrieval-augmented generation.
• Oversee agent context engineering to make knowledge consumable.
• At Senior Manager level, shape the method across engagements and hold broader authority.
• Fit assessed at interview.

Skills

Knowledge engineering

Semantic web

Ontology design

Taxonomy/data modeling

AI/LLM

Knowledge graph

RDF

SPARQL

Graph databases

SHACL

Neo4j

Amazon Neptune

Retrieval-augmented generation

Agent context engineering

Team leadership

Agile engineering

Education

Bachelor's degree (or equivalent)

Tools

RDF

SPARQL

Neo4j

Amazon Neptune

SHACL

Job description

Accenture is seeking an engineer to lead ontology work on knowledge-graph design and retrieval-augmented generation. You will drive schema and taxonomy design, construct the knowledge graph, and engineer agent context for efficient consumption of knowledge.

Travel up to 100% may be required depending on client needs. We value 5+ years in AI/LLM-related knowledge engineering, strong graph tech (RDF, SPARQL, graph DBs), and experience leading teams in agile contexts.