{"id":3245,"date":"2026-08-09T22:36:09","date_gmt":"2026-08-09T22:36:09","guid":{"rendered":"https:\/\/coderseditor.com\/itjobs\/job\/solution-architect-5\/"},"modified":"2026-08-09T22:36:09","modified_gmt":"2026-08-09T22:36:09","slug":"solution-architect-5","status":"publish","type":"job_listing","link":"https:\/\/coderseditor.com\/itjobs\/job\/solution-architect-5\/","title":{"rendered":"Solution Architect"},"content":{"rendered":"

Solution Architect Overview<\/h2>\n\n\n\n\n\n\n\n\n
Company Name<\/strong><\/td>\nCapgemini<\/td>\n<\/tr>\n
Job Role<\/strong><\/td>\nSolution Architect<\/td>\n<\/tr>\n
Qualifications<\/strong><\/td>\nNot Specified<\/td>\n<\/tr>\n
Category<\/strong><\/td>\nIT Jobs<\/td>\n<\/tr>\n
Job Type<\/strong><\/td>\nFull Time<\/td>\n<\/tr>\n
Location<\/strong><\/td>\nLondon<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

This position is for a Solution Architect focused on core banking and enterprise AI knowledge platform work. The role sits within Capgemini\u00e2\u0080\u0099s Architecture community and is aimed at an experienced professional who can shape and deliver advanced knowledge and retrieval capabilities for AI systems. The posting describes a hybrid working model, where time is split between company offices, client locations, and home, and it makes clear that the role cannot be performed from home all of the time.<\/p>\n

What you will be doing<\/h3>\n
    \n
  • Leading the design and implementation of an enterprise knowledge platform that supports AI agents operating across insurance, payments, and healthcare environments.<\/li>\n
  • Taking ownership of the architecture and governance of enterprise knowledge graphs, including ontology creation, semantic modelling, and graph-based retrieval design.<\/li>\n
  • Building and improving retrieval-augmented generation solutions, including GraphRAG patterns, to raise answer quality, improve grounding, and make responses more contextually relevant.<\/li>\n
  • Setting the standards for context engineering by defining how knowledge, instructions, and business rules are selected, organised, and presented to AI agents.<\/li>\n
  • Managing the full lifecycle of knowledge assets used by AI systems, from ingestion and curation through versioning, provenance tracking, freshness monitoring, and retirement of outdated material.<\/li>\n
  • Designing memory frameworks for agents that support episodic, semantic, and precedent-based retrieval.<\/li>\n
  • Creating permission-aware retrieval mechanisms with document-level security, identity propagation, multi-tenant separation, and detailed audit trails.<\/li>\n
  • Developing evaluation frameworks and automated testing pipelines to measure retrieval effectiveness, grounding quality, relevance, and the freshness of knowledge.<\/li>\n
  • Building data flywheel processes that turn operational and domain data into high-quality training and evaluation datasets for AI models.<\/li>\n
  • Working closely with product, engineering, security, and governance teams to deliver AI solutions that are scalable, compliant, and trustworthy.<\/li>\n
  • Defining platform standards, reusable architecture patterns, and best practices that can be adopted across several AI-powered product lines.<\/li>\n
  • Ensuring the platform complies with regulatory, privacy, and security requirements in highly regulated financial and healthcare settings.<\/li>\n<\/ul>\n

    What you need<\/h3>\n
      \n
    • Strong experience designing and implementing enterprise knowledge graphs, ontologies, and semantic data models.<\/li>\n
    • Deep practical knowledge of Retrieval-Augmented Generation, GraphRAG, hybrid search, and semantic retrieval architectures.<\/li>\n
    • Hands-on familiarity with vector databases, embedding technologies, reranking models, and retrieval optimisation methods.<\/li>\n
    • Solid understanding of context engineering, prompt orchestration, and token budget management for AI agents.<\/li>\n
    • Experience building and running AI knowledge management platforms with strong governance and auditability.<\/li>\n
    • Good knowledge of agentic AI architectures, multi-agent systems, and long-term memory frameworks.<\/li>\n
    • Experience with metadata management, data lineage, provenance tracking, and governance across the knowledge lifecycle.<\/li>\n
    • Practical experience with graph databases such as Neo4j, Amazon Neptune, TigerGraph, and ArangoDB.<\/li>\n
    • Experience with retrieval and search technologies including Azure AI Search, Elasticsearch, Pinecone, Weaviate, and Qdrant.<\/li>\n
    • Strong Python programming and data engineering skills, along with familiarity with modern data processing frameworks.<\/li>\n
    • Experience designing scalable ETL\/ELT pipelines and distributed data processing solutions.<\/li>\n
    • Knowledge of LLMOps, MLOps, AI evaluation frameworks, and model fine-tuning approaches.<\/li>\n
    • Experience implementing RBAC, ABAC, multi-tenant security models, and identity-aware retrieval systems.<\/li>\n
    • Strong understanding of compliance, privacy, auditability, and governance expectations in regulated sectors.<\/li>\n
    • Experience with cloud-native architectures using Azure, AWS, Kubernetes, Docker, and CI\/CD pipelines.<\/li>\n
    • Proven ability to lead platform strategy, drive enterprise architecture initiatives, and coordinate cross-functional engineering teams.<\/li>\n
    • Excellent communication, stakeholder management, and technology leadership skills.<\/li>\n
    • The role is advertised for an experienced professional, with a permanent contract in London, UK.<\/li>\n<\/ul>\n

      What Capgemini offers<\/h3>\n
        \n
      • A hybrid working setup that blends office, client-site, and home working.<\/li>\n
      • A workplace that has been recognised for wellbeing and that invests in employee support.<\/li>\n
      • Access to trained Mental Health Champions across the business.<\/li>\n
      • Wellbeing tools and apps, including Thrive and Peppy.<\/li>\n
      • A strong learning culture with extensive development opportunities, from think tanks to hackathons.<\/li>\n
      • Access to a very large learning library with many external certification options, including AWS, Microsoft, Harvard ManageMentor, and cybersecurity qualifications.<\/li>\n
      • Employment with a company recognised by Ethisphere as one of the World\u00e2\u0080\u0099s Most Ethical Companies for many consecutive years.<\/li>\n
      • The opportunity to join a global organisation that emphasises inclusion, sustainability, and responsible business.<\/li>\n
      • The chance to work alongside free-thinkers, entrepreneurs, and industry experts while helping clients use technology to innovate and grow.<\/li>\n<\/ul>\n

        Additional information<\/h3>\n

        Capgemini describes itself as an AI-powered global business and technology transformation partner with a long history, a large international workforce, and operations in more than 50 countries. The company says it delivers end-to-end services and solutions across strategy, technology, design, engineering, and business operations, supported by a broad partner ecosystem. The posting lists the role as a permanent position in London, with an experienced-professional level and a reference code of 530776. It was posted on 6 August 2026.<\/p>\n

        The company also states that it is a Disability Confident Employer at Level 2. As part of that commitment, candidates who declare a disability and meet the minimum essential criteria will be offered an interview, provided they opt in during the application process.<\/p>\n

        Applications can be submitted through the job posting\u00e2\u0080\u0099s apply-now process, including the option to start an application using LinkedIn.<\/p>\n\n

        Degree Requirement:<\/strong> Not Specified<\/p>\n

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