Knowledge Graph Engineer & AI Solutions Lead

Accenture Belgium; Brussel; On-site; EUR 80,000 - 120,000; Full time

Job summary

Accenture Belgium is seeking a strong knowledge engineer growing into a team lead to own the Knowledge Graph lifecycle from ingestion through deployment. You will design and implement AI/semantic solutions and collaborate with cross-functional teams to deliver end-to-end results.

Required: 2+ years in Knowledge Graph tech (RDF, SPARQL, KG curation), experience with graph databases, and Python ML tooling; leadership and client-facing consulting experience preferred.

Qualifications

• Bachelor's degree or equivalent
• Minimum 2 years of experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL)
• Minimum 2 years of experience in schema design, ontology management, and KG curation
• Minimum 2 years of designing and developing KG solutions and graph-based ML models
• Minimum 1 year of end-to-end data pipeline implementation for AI apps (esp. LLMs)
• Minimum 2 years of experience with relational databases, object stores, graph databases (e.g. Stardog, Neo4J, Neptune)

Responsibilities

• Build Knowledge Graph components for transforming a client's data architecture
• Design, develop, and implement AI and semantic solutions
• Collaborate with project team and delivery leads
• Build relationships with client counterparts on their workstream
• Assemble supporting evidence for the semantic layer solution
• Support Accenture sales efforts when called on
• Develop skills in cutting-edge Data & AI solutions and share with the team

Skills

Knowledge Graph

RDF

SPARQL

Ontology design

KG curation

Graph ML

Data pipeline for AI apps

Relational/Graph DBs

Cloud platforms

Python

TensorFlow/PyTorch

NLP/Search

Prompt engineering

Team lead experience

Consulting experience

Education

Bachelor's degree or equivalent

Tools

Stardog

Neo4J

Amazon Neptune

Apache NiFi

Airflow

Docker

Job description

Accenture Belgium is seeking a strong knowledge engineer growing into a team lead to own the Knowledge Graph lifecycle from ingestion through deployment. You will design and implement AI/semantic solutions and collaborate with cross-functional teams to deliver end-to-end results.

Required: 2+ years in Knowledge Graph tech (RDF, SPARQL, KG curation), experience with graph databases, and Python ML tooling; leadership and client-facing consulting experience preferred.