Knowledge Graph Architect for AI and Data Platforms

Reply; England; On-site; GBP 70,000 - 110,000; Full time

Job summary

Reply designs and builds semantic layers that give organisations a single, machine-readable view of their data. You will create ontologies and knowledge graphs across domains, connecting data, systems, and AI solutions from discovery to production.

The role emphasizes governance, scalable models, and productionising AI-powered features, including prompt engineering and evaluation, with strong collaboration across business and technical stakeholders.

Qualifications

• Experience delivering semantic layers, ontologies and knowledge graphs into production.
• Strong knowledge of RDF, OWL, SPARQL and Cypher.
• Proficient in Python for data integration and automation.
• Experience with Azure or cloud environments and data governance.

Responsibilities

• Design and build semantic models including ontologies and taxonomies.
• Develop and operate knowledge graphs end-to-end including ingestion and mapping pipelines.
• Standardise data across disparate systems using semantic technologies.
• Expose graph data via APIs and services for downstream consumers.
• Integrate knowledge graphs with AI solutions for analytics and generative AI use cases.
• Prototype and productionise AI-powered features, including prompt engineering and evaluation.
• Advise customers on semantic architecture, governance and best practices.

Skills

Semantic web

Python

Data architectures

Generative AI

LangChain

Stakeholder skills

Education

Degree in Computer Science or related

Tools

Neo4j

GraphDB

Cypher

SPARQL

LangChain

LlamaIndex

Git

CI/CD

Job description

Reply designs and builds semantic layers that give organisations a single, machine-readable view of their data. You will create ontologies and knowledge graphs across domains, connecting data, systems, and AI solutions from discovery to production.

The role emphasizes governance, scalable models, and productionising AI-powered features, including prompt engineering and evaluation, with strong collaboration across business and technical stakeholders.