AI Knowledge Engineer

Job Title: AI Knowledge Engineer

Knowledge Architecture | Semantic Systems | Enterprise AI

Build the trusted knowledge foundations that power enterprise AI assistants, RAG solutions, agentic systems and organisational memory. This hands-on role combines information architecture, semantic modelling, search and AI engineering.

Key Responsibilities

• Design enterprise taxonomies, ontologies, metadata frameworks and semantic models.
• Build and maintain knowledge graphs and semantic search architectures.
• Design and optimise RAG, Agentic RAG and GraphRAG solutions.
• Develop chunking, embedding, indexing, retrieval, reranking and grounding strategies.
• Implement vector databases and retrieval pipelines for structured and unstructured content.
• Build Python-based ingestion, enrichment and knowledge pipelines on cloud platforms.
• Define knowledge quality, governance, lineage, discoverability and lifecycle standards.
• Partner with domain experts to convert business knowledge into reusable AI-ready assets.
• Evaluate retrieval quality, answer groundedness and system performance using measurable criteria.

• Information architecture, data modelling, taxonomy design, ontology modelling and metadata strategy.
• Knowledge graphs, semantic modelling and semantic technologies such as RDF, OWL and SPARQL.
• RAG, Agentic RAG, GraphRAG, embeddings, vector databases and semantic search.
• Chunking strategies, retrieval optimisation, reranking and retrieval evaluation.
• Python programming, APIs, data pipelines and cloud-native engineering.
• Working knowledge of LLMs, agentic AI patterns and AI evaluation approaches.
• Strong critical thinking, structured problem-solving and stakeholder collaboration.

• 7+ years in data engineering, knowledge engineering, information architecture, search, cloud engineering or a related field.
• 3+ years building AI, LLM, RAG, knowledge graph or enterprise search solutions.
• Bachelors or Masters degree in Computer Science, Data Science, Information Systems or a related discipline, or equivalent practical experience.

• Azure AI Search, Azure OpenAI, Microsoft Fabric, Microsoft Graph or Copilot ecosystem experience.
• Experience with SharePoint, Microsoft 365, Confluence, ServiceNow or similar enterprise content platforms.
• Exposure to agent frameworks, graph databases, Responsible AI and knowledge governance.