Job Openings Sr Engineer Knowledge Graph

About the job Sr Engineer Knowledge Graph

We are seeking a visionary Senior Knowledge Graph & Context Engineer for the end-to-end design, build, deployment, and continuous improvement of the knowledge and context capabilities that power our AI assistants along with our enterprise search, and decision-support solutions. You will harness the context layer creation that will connect enterprise data, business knowledge, semantic models, and AI services, ensuring that product, ingredient, regulatory, quality, sustainability, marketing, and supply chain knowledge is delivered accurately, safely, and at speed through reusable and scalable solutions. The ideal candidate will be part of our enterprise insights and transformation agenda, helping translate fragmented knowledge assets across source systems, such as ERP , CRM , PLM, PIM/MDM, LIMS, Regulatory, DAM, and SCM, into trusted, reusable, and governed context packs for Agentic AI use cases. The position requires a blend of business understanding, semantic / knowledge engineering capability, and AI delivery expertise, with a strong focus on enabling high-quality grounding, retrieval, governance, and adoption across the organization.

YOUR NEW KEY RESPONSIBILITIES:

  • Design, build, and operationalize the enterprise context layer that supports AI assistants, semantic search, and decision-support solutions across business domains.
  • Transform enterprise knowledge assets into reusable, trusted, and scalable context packs for Agentic AI outcomes.
  • Design and optimize retrieval pipelines, grounding patterns, chunking strategies, metadata enrichment, and prompt/context orchestration to ensure accurate, relevant, and safe AI responses.
  • Partner closely with Ontology Engineers, AI Engineers, and Data teams to apply semantic enrichment, taxonomies, controlled vocabularies, and relationship modelling that improve discoverability, interoperability, and reasoning.
  • Embed policy-aware controls, access rules, governance standards, and quality checks into context pipelines to ensure compliant and trusted use of enterprise knowledge.
  • Work with Data Platform and Engineering teams to productionize context services across graph, search, and AI ecosystems, ensuring performance, scalability, monitoring, and maintainability.
  • Partner with Product, Data Platform, Security / Compliance, Architecture, and business domain teams to align priorities with business needs and accelerate adoption of AI-enabled knowledge solutions.
  • Help improve findability, reuse, decision quality, and business efficiency, while tracking impact, adoption, and value realization.
  • Support the embedding of knowledge-driven and AI-enabled processes into business workflows, tools, and digital products.
  • Drive continuous improvement in knowledge quality, retrieval effectiveness, semantic consistency, and AI response performance.

ARE THESE YOUR SECRET INGREDIENTS?

  • BSc or MSc in a relevant field such as Computer Science, Information Science, Data Science, Artificial Intelligence, Knowledge Engineering, Computational Linguistics, or a related discipline.
  • 5+ experience in knowledge engineering, context engineering, semantic technologies, enterprise search, GenAI / LLM solutions, or AI product enablement.
  • Strong understanding of one or more of the following: ontologies, taxonomies, controlled vocabularies, knowledge graphs, metadata modelling, semantic enrichment, and information retrieval.
  • Hands-on experience designing or supporting RAG pipelines, prompt / grounding patterns, context orchestration and memory management, context quality and provenance, semantic search, and evaluation of AI responses.
  • Experience with relevant technologies such as graph databases, vector / search platforms, semantic web technologies, and cloud AI / data ecosystems. Exposure to tools and W3C standards such as RDF, OWL, SKOS, SHACL, SPARQL, Neo4j, Stardog, Ontotext GraphDB, Azure ecosystem, or equivalent, is considered a strong advantage.
  • Experience working with enterprise knowledge and data domains such as PLM, PIM / MDM, LIMS, Regulatory, DAM, ERP, SCM, or other structured and unstructured business data sources.
  • Strong influencing, interpersonal, and communication skills, with the ability to work effectively across Data, AI, Technology, and business functions.
  • Experience presenting solutions, trade-offs, and recommendations to senior management and technical leadership teams.

Job Model: Hybrid "1 day only WFH"/ New Cairo