Knowledge Graph Lead: AI Ontology & RAG

Accenture PLC; Sacramento (CA); On-site; USD 94,000 - 294,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision

Life insurance

Long-term disability

401(k)

Paid holidays

Paid time off

Job summary

Accenture is seeking a seasoned knowledge engineer in the United States to lead ontology work, schema and taxonomy design, and knowledge-graph construction on a single engagement. You will drive retrieval-augmented generation and agent context engineering in production, shaping the method as you progress to senior levels.

The role requires 5+ years in knowledge engineering and hands-on graph technologies, with strong collaboration in agile engineering teams and client-facing delivery.

Qualifications

• 5+ years hands-on knowledge engineering, semantic web, ontology design, or taxonomy/data modeling with 1–2 years AI/LLM work.
• 3+ years knowledge graph technologies (RDF, SPARQL, property graphs) and graph databases such as Neo4j or Neptune.
• 1+ year experience with retrieval-augmented generation and agent context engineering in production.

Responsibilities

• Lead ontology work: schema and taxonomy design, knowledge-graph construction, RAG, and agent context engineering on engagements.
• Shape method at Senior Manager level across engagements; assess fit at interview.

Skills

Knowledge engineering

Semantic web

Ontology design

Taxonomy data modeling

Knowledge graph technologies

RDF/SPARQL

Graph databases

Retrieval-augmented generation

Team leadership

Agile engineering

Education

Bachelor's degree or equivalent (12 years)

Associate degree + 6 years experience

Tools

Neo4j

Amazon Neptune

SHACL

Qdrant/Pinecone

Job description

Accenture is seeking a seasoned knowledge engineer in the United States to lead ontology work, schema and taxonomy design, and knowledge-graph construction on a single engagement. You will drive retrieval-augmented generation and agent context engineering in production, shaping the method as you progress to senior levels.

The role requires 5+ years in knowledge engineering and hands-on graph technologies, with strong collaboration in agile engineering teams and client-facing delivery.