Knowledge Engineering Manager

About the role

You will lead a significant knowledge engineering scope and function within a large program, actively contributing to thought leadership. You will shape how a substantial body of work formulates real‑world problems into scalable AI and knowledge‑graph solutions and set the technical direction for that scope.

Key responsibilities

• Lead the build of Knowledge Graph solutions that transform the client’s data architecture within the program scope.
• Direct the design, development, and implementation of AI and semantic solutions, ensuring seamless integration of all components.
• Collaborate with project leaders, delivery leads, and client stakeholders to create graph‑powered Data & AI offerings.
• Develop strong client relationships and earn the trust of key advisors.
• Make the business case for the recommended semantic‑layer solution.
• Contribute to Accenture’s sales and pre‑sales efforts.
• Provide thought leadership on technology trends, new opportunities, innovations, and associated risks.

Required profile

• Bachelor’s degree or equivalent, plus at least four of the following: experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL), schema design, ontology management, KG curation.
• Proven ability to design and develop KG solutions and graph‑based machine‑learning models.
• Experience implementing end‑to‑end data pipelines for AI applications, especially large language models.
• Strong knowledge of relational databases, object stores, graph databases (Stardog, Neo4j, Amazon Neptune) and vector databases, and experience leading a team or workstream.

Required skills

• RDF, SPARQL, LPG, SHACL
• Ontology management and schema design
• Graph databases (Stardog, Neo4j, Amazon Neptune) and vector databases
• Python with TensorFlow, PyTorch
• Data‑pipeline tools such as Apache NiFi and Airflow
• Cloud platforms (AWS, Azure, GCP)
• NLP, search techniques, prompt engineering, and enterprise‑scale LLM applications