Hybrid AI Knowledge Graph Engineer

Capgemini; England; Hybrid; GBP 70,000 - 105,000; Full time

Job summary

Capgemini is seeking a specialist to build and operate the knowledge graph and retrieval stack for our AI-native product organisation within Financial Services. You will own production graph schemas, ontology, entity resolution, and scalable pipelines across client estates.

You will implement end-to-end retrieval, hybrid search, and secure data contracts, ensuring regulatory compliance and multi-tenant safeguards. A strong data engineering and graph background is essential for success.

Qualifications

• Production data engineering: Python, SQL, and a pipeline orchestration framework.
• Graph engineering: schema/ontology modelling, production graph database, graph query language.
• Entity resolution across systems and regulated data discipline.

Responsibilities

• Build knowledge graph in production, including ontology, schema, entity resolution, and refresh pipelines.
• Develop graph retrieval as a first-class capability with efficient traversal and ranking.
• Oversee end-to-end retrieval stack: chunking, embedding, hybrid search, and alerts.
• Create data pipelines from client systems with ingestion, mapping, quality checks, and monitoring.
• Ensure an immutable audit trail and govern data contracts between pipelines.
• Implement permission-aware access and multi-tenant isolation.
• Design data for the agent memory plane and governance rules.
• Coordinate with platform teams to align contracts and data models.

Skills

Python

SQL

Neo4j

Graph databases

Data pipelines

Entity resolution

Retrieval systems

PII/PHI handling

AI coding assistants

Tools

PostgreSQL

pgvector

ClickHouse

Neo4j Enterprise

Job description

Capgemini is seeking a specialist to build and operate the knowledge graph and retrieval stack for our AI-native product organisation within Financial Services. You will own production graph schemas, ontology, entity resolution, and scalable pipelines across client estates.

You will implement end-to-end retrieval, hybrid search, and secure data contracts, ensuring regulatory compliance and multi-tenant safeguards. A strong data engineering and graph background is essential for success.