Lead AI Architect

Job Title : Lead AI Architect - Financial Services Location : London About the Job you are considering: we are seeking a highly experienced Lead AI Architect to drive the design, architecture, and deployment of enterprise-scale AI solutions within regulated financial services environments. This role will combine strategic architecture leadership with hands-on technical delivery, helping clients transition AI initiatives from proof-of-concept to robust, scalable, and governed production solutions. The successful candidate will define reusable AI engineering foundations, establish architecture standards, and lead complex client engagements across Banking, Insurance, and Capital Markets. They will work closely with engineering, data, risk, compliance, and executive stakeholders to ensure AI systems are explainable, secure, cost-effective, and compliant with regulatory expectations. Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time. Your Role: AI Solution Architecture & Delivery • Lead the architecture, design, and implementation of enterprise AI and Generative AI solutions within regulated financial services organizations. • Partner with client engineering, data, security, and risk teams to operationalize AI solutions and move them into production environments. • Define end-to-end AI architecture covering data ingestion, retrieval, orchestration, model serving, governance, and monitoring. • Design scalable AI/ML platforms leveraging cloud-native services and modern data architectures. • Ensure AI solutions operate within agreed governance, security, and compliance frameworks. • Conduct architecture reviews and provide technical leadership throughout project lifecycle. • Lead technical workshops, demonstrations, and architecture discussions with CIOs, CTOs, CDOs, Risk Leaders, and Engineering Teams. Data, Context & Control Architecture • Design robust data foundations supporting AI workloads, including semantic layers, knowledge graphs, vector databases, and retrieval systems. • Establish architectures that ensure AI models leverage trusted and governed enterprise data. • Define data lineage, traceability, and auditability requirements for AI-driven business processes. • Implement architecture patterns supporting explainability, transparency, and responsible AI adoption. AI Governance, Evaluation & Observability • Develop frameworks for AI model evaluation, validation, monitoring, and continuous improvement. • Define standards for model performance testing, bias detection, hallucination management, and output quality assessment. • Implement observability frameworks using industry-leading tools and OpenTelemetry-based tracing. • Establish production monitoring mechanisms covering performance, risk, cost optimization, and operational resilience. Reusable Assets & Engineering Standards • Build reusable AI accelerators, reference architectures, design patterns, and engineering blueprints. • Define AI architecture standards, governance frameworks, and delivery methodologies across the Financial Services practice. • Create technical documentation, architecture artifacts, and implementation playbooks. • Mentor architects, engineers, and delivery teams in AI best practices and enterprise architecture principles. Technology Strategy & Innovation • Evaluate emerging AI platforms, frameworks, and technologies for enterprise adoption. • Work closely with strategic technology partners including cloud providers and AI platform vendors. • Identify opportunities to leverage existing capabilities rather than custom-building solutions unnecessarily. • Contribute to AI thought leadership, innovation initiatives, and practice development activities. Your Skills: Essential • 10+ years of experience designing, architecting, and delivering enterprise Data, Analytics, AI, or Machine Learning solutions. • Proven experience deploying AI/ML solutions into production environments at enterprise scale. • Strong hands-on architecture experience across: • Generative AI • Large Language Models (LLMs) • Retrieval-Augmented Generation (RAG) • AI Agents / Agentic Architectures • MLOps and LLMOps • Expertise with enterprise data platforms such as: • Databricks • Snowflake • Azure Data Platform • AWS Data & AI Services • Google Cloud AI Platforms • Experience designing knowledge retrieval architectures including vector databases, semantic search, and metadata-driven architectures. • Strong understanding of cloud architecture, microservices, APIs, and event-driven architectures. • Experience establishing AI governance, model monitoring, evaluation frameworks, and observability practices. • Demonstrated experience in Financial Services, Banking, Insurance, Capital Markets, or another highly regulated industry. • Strong knowledge of enterprise security, data privacy, risk management, and regulatory controls. • Experience leading architecture reviews, technical governance forums, and executive stakeholder engagements. • Ability to communicate complex technical concepts clearly to both technical and non-technical audiences. Desirable • Product engineering or AI platform product development experience. • Experience with Agentic AI frameworks and Model Context Protocol (MCP). • Knowledge of OpenTelemetry and observability solutions for AI workloads. • Exposure to Responsible AI frameworks and AI governance regulations. • Consulting and client-facing delivery experience within global organizations. • Public speaking, thought leadership, blogging, or technical publication experience. • Financial Services domain certifications or cloud architecture certifications. We are a Disability Confident Employer: Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Co