Knowledge Engineer

The Centre for Advanced Data (C4AD) is Accenture's specialist centre of excellence that sets the architecture standard for modern, AI-ready data estates across APAC, and mobilises the talent to deliver them at scale.

The C4AD operates across three core disciplines: Master Data Architecture, Knowledge Engineering, and Data Products. Every practitioner in the C4AD is expected to apply agentic and generative techniques as the default way of working, not as an add-on. The centre supports large-scale data and AI transformation programmes across the region, ranging from enterprise data modernisation to AI-ready platform builds.

Join the Centre for Advanced Data APAC as a Knowledge Engineer, where you will own ontology and semantic strategy across engagements, set the knowledge-engineering standards for the practice, and assure the semantic layers that ground enterprise AI. You will define how the C4AD approaches knowledge representation across programmes, and hold the line on quality, consistency, and semantic integrity as those programmes scale.

You will work closely with Data Architects and AI Engineers, ensuring that the ontologies and knowledge graphs you define and govern give AI systems something real, structured, and reliable to reason over.

• →Own ontology and semantic strategy across C4AD engagements, setting the approach, standards, and quality bar for knowledge engineering across the practice.
• →Assure semantic layers that ground enterprise AI, reviewing, governing, and signing off on the ontological structures that AI systems in our programmes reason over.
• →Design, develop, and govern enterprise ontologies, taxonomies, and knowledge graphs that accurately represent business domains, their relationships, and the rules that govern them.
• →Build and govern semantic models using RDF/OWL, SHACL, and SPARQL, and property graph approaches using platforms such as Neo4j, Amazon Neptune, or Stardog.
• →Apply and adapt industry-standard ontologies (e.g. FIBO, BIAN, GS1, TM Forum) to meet organisation-specific semantic requirements.
• →Develop and enforce semantic modelling standards, naming conventions, versioning, and curation workflows, and drive adoption of those standards across delivery teams.
• →Enable AI and ML applications through knowledge graph enrichment, entity resolution, semantic search, and ontology-powered RAG pipelines.
• →Engage business SMEs and domain experts to elicit and formalise implicit business rules, relationships, and concepts into explicit ontological structures.

• 5+ years of experience in knowledge engineering, ontology design, or semantic modelling, with a track record of owning the knowledge engineering approach on complex programmes, not just contributing to it.
• Proven deep expertise in ontology engineering, authoring OWL ontologies, RDFS schemas, SHACL constraint shapes, and SPARQL queries, with real enterprise delivery behind it.
• Hands-on experience with graph databases and knowledge graph platforms such as Neo4j, Amazon Neptune, Stardog, or GraphDB.
• Proficiency with semantic tooling including Protégé, TopBraid Composer, or equivalent ontology authoring environments.
• Strong understanding of how semantic models connect to downstream data products, metadata catalogues, and AI/ML enrichment workflows, and the ability to assure that integration is sound.
• Knowledge of property graph modelling and the ability to move between RDF-based and property graph paradigms depending on platform and use case.
• Experience with entity resolution, semantic search, and knowledge-driven RAG architectures.
• Experience working within modern data architectures including data mesh, data lakehouse, and federated governance models.
• Background in linked data principles (W3C standards) and LLM grounding techniques, including GraphRAG and ontology-grounded generation, and practical experience applying them in enterprise contexts.
• Industry experience in Financial Services, Government, Health, Energy, or Utilities sectors in APAC is highly regarded.
• Good communication skills with the ability to engage both technical teams and business SMEs.

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