Jobs / Capgemini
AI Cloud DevOps & Platform Engineer - London, UK
Capgemini · London, ENG, United Kingdom
London, ENG, United KingdomExp: 5+ yrsHybrid
Remuneration
Not specified
Location
London, ENG, United Kingdom
Visa sponsorship
Not specified
Job summary
Deploys, operates, and optimizes production AI, machine learning, and generative AI platforms across AWS and Azure. The role combines AIOps, Platform Engineering, and DevOps to build automated infrastructure and CI/CD pipelines, manage LLM, RAG, agent, and Copilot solutions, monitor reliability and model performance, and support AI security, governance, and compliance.
Benefits
Wellbeing appsTraining and development opportunitiesAccess to 250,000 coursesExternal certification opportunities
Qualifications
- At least 5 years of DevOps and Platform Engineering experience and 3 years of AIOps experience.
- Strong experience with Azure and/or AWS.
- Production experience supporting AI, machine learning, or generative AI solutions.
- Knowledge of Azure OpenAI, Azure AI Services, Amazon Bedrock, and/or SageMaker.
- Understanding of LLMs, RAG architectures, AI agents, and modern AI patterns.
- Experience with Platform Engineering, DevOps, and cloud operations.
- Expertise in CI/CD, Infrastructure as Code, and automation.
- Proficiency in Python and scripting.
- Experience with Docker, Kubernetes, GitHub Actions, and/or Azure DevOps.
- Knowledge of monitoring, observability, reliability engineering, and operational support.
- Experience in regulated or large-scale enterprise environments.
- Consulting experience delivering cloud, platform, or AI transformation initiatives.
Responsibilities
- Deploy, operate, and support AI, machine learning, and generative AI solutions across AWS and Azure.
- Implement and manage LLM, RAG, AI agent, and Copilot-based solutions.
- Build and maintain CI/CD pipelines, infrastructure automation, and operational tooling.
- Monitor platform health, model performance, reliability, and operational SLAs.
- Troubleshoot incidents, perform root cause analysis, and drive service improvements.
- Support AI governance, security, compliance, and Responsible AI requirements.
- Collaborate with architects, engineers, and business stakeholders to operationalize AI solutions.
- Contribute to AI platform strategy, standardization, and best practices.
Skills
AWSAzureAzure DevOpsBicepCloudFormationDatabricksDockerGitHubGitHub ActionsKubernetesMakePythonTerraform
Certifications
Azure AI Engineer AssociateAzure DevOps Engineer ExpertAWS AI PractitionerAWS Machine Learning Engineer or SpecialtyAWS DevOps Engineer ProfessionalKubernetes CKA or CKAD
Languages
Python
Industry
Artificial intelligenceCloud computingTechnology consulting
Relocation
No