Hybrid DevOps AI Platform Architect - London

Capgemini; Greater London; Hybrid; GBP 120,000 - 170,000; Full time

Job summary

Capgemini is seeking a DevOps AI Platform Architect to design, build, and optimize scalable AI platforms enabling efficient AI/ML development, deployment, and governance. The role blends cloud, DevOps, automation, and AI to accelerate business value across hybrid environments.

You will work with Azure, AWS, or Google Cloud, establish CI/CD and MLOps pipelines, and ensure security and cost optimization while collaborating with data scientists and security teams to deliver enterprise-grade AI

Qualifications

• Define and document global AI platform patterns, Discovery Zone BYOD end-to-end ML lifecycle reference architectures and obtain approvals through architecture forums.
• Design Model Serving Architecture.
• Partner with the AI Tech Lead on the Model Serving PoC and define the end-to-end architecture for scalable and secure model deployment.
• Define MLOps Architecture.
• Define and document MLOps architecture using learnings from the Model.
• Serving PoC and drive approvals for standardization.
• Enable LLM Strategic Capabilities.
• Assess different capabilities for LLM Azure AI Foundry Bedrock and Databricks and take design decisions for approval.
• Work with security, Data protection office, other architecture teams to align them with the decision and secure approvals for roll out.
• Document the low level design for LLM roll out to different use case.
• Evolve Platform Capabilities, Drive incremental platform capabilities (Responsible AI, GenAI, Data Governance) aligned with the approved L2 architecture.

Responsibilities

• Designing and implementing AI platform architectures using cloud services such as Microsoft Azure, AWS, or Google Cloud.
• Establishing CI/CD and MLOps pipelines to automate model training, testing, deployment, and monitoring.
• Managing containerized workloads using Docker and Kubernetes for scalability and reliability.
• Ensuring platform security, compliance, governance, and cost optimization through best practices and automation.
• Collaborating with data scientists, developers, security teams, and business stakeholders to deliver enterprise-grade AI solutions.
• Implementing observability, monitoring, and incident management processes to maintain platform performance and availability.
• Evaluating and integrating emerging technologies in Generative AI, platform engineering, and cloud-native ecosystems to drive innovation.

Skills

AI platform patterns

Model Serving Architecture

MLOps Architecture

LLM capabilities

Cloud platforms

Security & Governance

Observability & incident mgmt

Stakeholder collaboration

Job description

Capgemini is seeking a DevOps AI Platform Architect to design, build, and optimize scalable AI platforms enabling efficient AI/ML development, deployment, and governance. The role blends cloud, DevOps, automation, and AI to accelerate business value across hybrid environments.

You will work with Azure, AWS, or Google Cloud, establish CI/CD and MLOps pipelines, and ensure security and cost optimization while collaborating with data scientists and security teams to deliver enterprise-grade AI