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About the Role

You will own the knowledge layer for three product lines, focusing on the enterprise knowledge graph, governed retrieval plane, context engineering, and knowledge lifecycle management. This is a platform leadership role with a governance mandate.

Responsibilities

• Own the enterprise knowledge graph, including ontology and schema design, pipelines for building and refreshing it, and graph retrieval as a platform capability.
• Optimize RAG end-to-end, including chunking and embedding strategy, hybrid and graph-augmented retrieval, reranking, and evaluation harnesses.
• Establish context engineering as a platform discipline, defining what enters each agent's context window and how it is composed.
• Manage the knowledge lifecycle for AI systems, from source documents to governed, versioned knowledge agents.
• Develop the agent memory plane for writing, recalling, and governing episodic and precedent memory.
• Implement permission-aware retrieval with document-level access controls, multi-tenant isolation, and an audit trail.
• Build the data flywheel for model adaptation using curated and governed production data for LLM and SLM tuning.

Requirements

• Graph engineering depth: designed ontologies and graph schemas, operated production graph systems (Neo4j or comparable), including graph retrieval for AI workloads.
• Experience building and optimizing production RAG pipelines (embedding strategy, hybrid search, reranking, retrieval evaluation).
• Context engineering fluency: experience building context assembly, compaction, or agent memory systems.
• Knowledge management for AI: experience with curation, provenance, and versioning of enterprise knowledge for machine consumption.
• Regulated-data credentials: experience operating under financial-services data regulation or GDPR, with the ability to design for auditability.
• Technical leadership to set standards for senior engineers without direct reporting lines.
• Daily, hands-on use of AI tools in your own work.

Skills

• Graph engineering
• RAG optimization
• Context engineering
• Knowledge management for AI
• Graph data science
• AI governance

Location

• Hybrid

Work Type

• Hybrid working

Experience Level

• Senior

Benefits

• Peer Recognition Portal called Applaud
• Accredited Great Place to Work for Wellbeing in 2024
• Trained ‘Mental Health Champions’
• Wellbeing apps such as Thrive and Peppy
• Countless training and development opportunities
• Access to 250,000 courses with numerous external certifications

About the Company

• NewCo is a new AI-native product organisation within Capgemini Financial Services.
• We build products, not projects: software for insurance claims, payment operations, and health operations, sold to banks, insurers, and health plans.
• Our engineering model is agentic: engineers author the specifications, tooling, evaluation suites, and guardrails, and AI agents do most of the implementation.
• Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value.
• We imagine the future of organisations and make it real with AI, technology and people.
• With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries.
• We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations.
• The Group reported 2024 global revenues of €22.1 billion.

Equal Opportunity

• We are a Disability Confident Employer
• Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme.
• As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who: Declare they have a disability, and Meet the minimum essential criteria for the role.
• Please opt in during the application process.