Lead Knowledge Engineer: Graph AI & LLM Solutions

Accenture; Raleigh (NC); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Medical, dental, vision benefits

401(k) plan

Job summary

Accenture is seeking a Knowledge Engineer to translate real-world problems into scalable AI and Knowledge Graph solutions for enterprise clients. You will lead a team, guide methodology choices, and shape architectures leveraging LLMs, RDF/ SPARQL, and graph databases.

You’ll work with business and technical stakeholders to justify the value of semantic layers, design ontologies, and deliver end-to-end Data & AI offerings across client engagements.

Qualifications

• Bachelor’s degree or equivalent (min 12 years work experience).
• Minimum 4 years designing and developing knowledge graph solutions.
• 3 end-to-end data pipelines for AI applications, including LLMs.
• 6+ years with graph databases and Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL).

Responsibilities

• Build Knowledge Graph solutions that transform clients’ data architecture.
• Design, develop, and implement AI and semantic solutions and ensure integration.
• Work with project teams and client stakeholders to create stand-out Data & AI offerings based on graph tech.
• Develop strong client relationships and demonstrate value of semantic layers.
• Make the business case for semantic layer solutions and support pre-sales when needed.
• Continuously learn and lead in cutting-edge Data & AI solutions.

Skills

Knowledge Graphs

Graph Databases

SPARQL

RDF

Ontology design

Python

LLMs

NLP techniques

Pre-sales

Client engagement

Education

Bachelor’s degree or equivalent (min 12 years experience)

Tools

Stardog

Neo4J

Amazon Neptune

Job description

Accenture is seeking a Knowledge Engineer to translate real-world problems into scalable AI and Knowledge Graph solutions for enterprise clients. You will lead a team, guide methodology choices, and shape architectures leveraging LLMs, RDF/ SPARQL, and graph databases.

You’ll work with business and technical stakeholders to justify the value of semantic layers, design ontologies, and deliver end-to-end Data & AI offerings across client engagements.