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Capgemini

Global consulting, technology services, outsourcing

Lead AI Architect

Applied Machine LearningUpdated on Nov 14
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • At least 10 years of experience designing, architecting, and delivering enterprise data, analytics, artificial intelligence, or machine learning solutions.
  • Proven experience deploying artificial intelligence or machine learning solutions into production environments at enterprise scale.
  • Hands-on architecture experience across generative artificial intelligence, large language models, retrieval-augmented generation, artificial intelligence agents or agentic architectures, and machine learning operations or large language model operations.
  • Expertise with enterprise data platforms such as Databricks, Snowflake, Azure Data Platform, AWS Data and AI Services, or Google Cloud AI Platforms.
  • Experience designing knowledge retrieval architectures, including vector databases, semantic search, and metadata-driven architectures.
  • Strong understanding of cloud architecture, microservices, application programming interfaces, and event-driven architectures.
  • Experience establishing artificial intelligence governance, model monitoring, evaluation frameworks, and observability practices.
  • 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 technical and non-technical audiences.

Responsibilities

  • Lead the architecture, design, and implementation of enterprise artificial intelligence and generative artificial intelligence solutions within regulated financial services organizations.
  • Partner with client engineering, data, security, and risk teams to operationalize artificial intelligence solutions and move them into production environments.
  • Define end-to-end artificial intelligence architecture covering data ingestion, retrieval, orchestration, model serving, governance, and monitoring.
  • Design scalable artificial intelligence and machine learning platforms leveraging cloud-native services and modern data architectures.
  • Ensure artificial intelligence solutions operate within agreed governance, security, and compliance frameworks.
  • Conduct architecture reviews and provide technical leadership throughout the project lifecycle.
  • Lead technical workshops, demonstrations, and architecture discussions with chief information officers, chief technology officers, chief data officers, risk leaders, and engineering teams.
  • Design robust data foundations supporting artificial intelligence workloads, including semantic layers, knowledge graphs, vector databases, and retrieval systems.
  • Establish architectures that ensure artificial intelligence models leverage trusted and governed enterprise data.
  • Define data lineage, traceability, and auditability requirements for artificial intelligence-driven business processes.
  • Implement architecture patterns supporting explainability, transparency, and responsible artificial intelligence adoption.
  • Develop frameworks for artificial intelligence 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.
  • Build reusable artificial intelligence accelerators, reference architectures, design patterns, and engineering blueprints.
  • Define artificial intelligence 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 artificial intelligence best practices and enterprise architecture principles.
  • Evaluate emerging artificial intelligence platforms, frameworks, and technologies for enterprise adoption.
  • Work closely with strategic technology partners, including cloud providers and artificial intelligence platform vendors.
  • Identify opportunities to leverage existing capabilities rather than custom-building solutions unnecessarily.
  • Contribute to artificial intelligence thought leadership, innovation initiatives, and practice development activities.

Desired Qualifications

  • Product engineering or artificial intelligence platform product development experience.
  • Experience with agentic artificial intelligence frameworks and Model Context Protocol.
  • Knowledge of OpenTelemetry and observability solutions for artificial intelligence workloads.
  • Exposure to responsible artificial intelligence frameworks and artificial intelligence 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.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1967

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