AI Architect

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

Your Role

As an AI Architect, you will own the architecture and industrialization of AI capabilities across the full spectrum — from Generative AI and Agentic AI to Computer Vision, local and cloud models, and AI-enabled business processes. You will be the connective tissue between business requirements, data, models, infrastructure, security and operations — ensuring every AI solution is measurable, governed, secure and production-ready.

In this role you will play a key role in:

• Defining target architectures for LLM, RAG, Agentic AI, Computer Vision and multimodal capabilities, including agent design, memory, function calling, human-in-the-loop controls and multi-agent patterns
• Architecting and implementing AI and business-process orchestration solutions using platforms such as Langflow and Flowable, translating complex business processes into executable workflows that integrate people, AI agents, APIs and enterprise systems using BPMN 2.0
• Establishing and governing the AI evaluation strategy, including Golden Dataset methodology, task-specific metrics, benchmarking, regression evaluation and maintaining clear separation between training and evaluation data
• Defining production observability frameworks covering drift detection, quality degradation monitoring, feedback loops and continuous re-evaluation of approved AI solutions
• Designing local and sovereign model architectures using Ollama, vLLM and the Hugging Face ecosystem, evaluating quality, security, sovereignty, cost and operational trade-offs between local and managed models
• Defining RAG pipelines including ingestion, chunking, embedding, vector search, hybrid retrieval and reranking, as well as Computer Vision pipelines for classification, detection, segmentation and anomaly detection
• Governing the full MLOps and LLMOps lifecycle — from development and evaluation through to deployment, observation and continuous improvement — while embedding security, Responsible AI principles and architectural governance throughout
• Acting as the AI architecture authority within the solution, aligning with the Lead Solution Architect, guiding AI/ML and Computer Vision engineers, and communicating clearly with non-technical stakeholders
  
  
  

Your Profile

• Proven experience as an AI Architect or senior technical architect with 8–12 years of hands-on experience across GenAI, LLM, RAG and Agentic AI, with practical application of IAF, TOGAF or an equivalent recognised architecture framework
• Strong command of AI engineering fundamentals including Python, REST APIs, vector databases, GPU/inference concepts, containerisation and cloud AI platforms, with experience governing MLOps and LLMOps pipelines end-to-end
• Demonstrated ability to define and operationalise AI evaluation strategies, including Golden Dataset design, model benchmarking, drift detection and observability — balancing AI autonomy with deterministic controls and human accountability
• Experience architecting AI and business-process orchestration solutions using tools such as Langflow, LangChain, LangGraph or Flowable, with solid understanding of BPMN 2.0 and the ability to translate business processes into governed, scalable AI-integrated workflows
• Strong stakeholder communication skills with the ability to challenge model and platform choices using evidence-based evaluation, and to influence both technical teams and senior business leaders
• Experience in security and Responsible AI by design, including secure model endpoints, guardrails, controlled tool access and appropriate explainability practices
  
  
  

What You'll Love About Working Here

• Dedicated innovation labs We help the world's largest innovators engineer the products and services of tomorrow by leveraging our experts and labs, dedicated to topics as 5G, 6G, AI, Autonomous Vehicles and Quantum.
• Digital campuses and academy Our engineering academy offers more than 60,000 hours of training, as well as our digital campus on GenAI, data or sustainability, supporting digital learning in the flow of work from awareness to expert certifications.
• Worldwide Leader of Engineering Services Capgemini Engineering combines its broad industry knowledge and cutting-edge technologies in digital and software to support the convergence of the physical and digital worlds. We help our clients unleash their R&D potential to develop smart products and services of tomorrow.
• Engineering Horizons A global conference crafted exclusively for Capgemini Engineering colleagues, where excellence takes centre stage. Immerse yourself in opportunities to showcase your talents and connect with the brightest minds in engineering across the planet.
  
  
  

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.