AI Knowledge Graph Manager & Ontology Architect

Accenture PLC; Des Moines (IA); On-site; USD 120,000 - 220,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) plan

Bonus opportunities

Paid holidays

Paid time off

Job summary

Accenture is seeking an experienced engineer to lead ontology work for a major engagement, building schema, taxonomy, and knowledge graphs while enabling retrieval-augmented generation and context engineering for AI agents.

The role requires 5+ years in knowledge engineering and 1–2 years in AI/LLM projects, plus 2+ years leading teams and 3+ years with graph technologies. Travel may be required as needed across client engagements.

Qualifications

• 5+ years in knowledge engineering, semantic web, ontology design, or taxonomy/data modeling, with 1–2 years in AI/LLM work.
• 3+ years with knowledge graph technologies (RDF, SPARQL, property graphs) and graph databases such as Neo4j or Neptune.
• AI-adjacent experience with 1–2 years of LLM work.
• 1 year of experience with retrieval-augmented generation and agent context engineering in production or near-production contexts.
• 2+ years leading a team or workstream within a larger program.
• 5+ years of experience in agile engineering or consulting teams.
• Bachelor's degree or equivalent (12 years) work experience (or 6 years if Associate's degree).

Responsibilities

• Lead ontology design and knowledge-graph construction on a single engagement.
• Oversee retrieval-augmented generation and agent context engineering in production environments.
• Shape the method across engagements and provide leadership within the team.
• Travel as required by business needs (0–100%).

Skills

Knowledge engineering

Semantic web

Ontology design

Taxonomy/data modeling

Retrieval-augmented generation

Knowledge graph technologies

Education

Bachelor's degree

Tools

Neo4j

Amazon Neptune

RDF

SPARQL

SHACL

Job description

Accenture is seeking an experienced engineer to lead ontology work for a major engagement, building schema, taxonomy, and knowledge graphs while enabling retrieval-augmented generation and context engineering for AI agents.

The role requires 5+ years in knowledge engineering and 1–2 years in AI/LLM projects, plus 2+ years leading teams and 3+ years with graph technologies. Travel may be required as needed across client engagements.