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About the Role
We are seeking a highly skilled AI Cloud DevOps & Platform Engineer responsible for the deployment, operation, and continuous optimization of AI, Machine Learning, and Generative AI solutions across AWS and Azure. This role combines AIOps, Platform Engineering, and DevOps capabilities to ensure AI platforms are secure, scalable, resilient, and production-ready.
Responsibilities
- Deploy, operate, and support AI, ML, 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 adoption of best practices.
Requirements
- 5+ Years on DevOps & Platform Engineering, 3+ on AI Ops
- Strong experience with Azure and/or AWS cloud platforms.
- Hands-on experience supporting AI, ML, or Generative AI solutions in production.
- Knowledge of Azure OpenAI, Azure AI Services, Amazon Bedrock, and/or SageMaker.
- Understanding of LLMs, RAG architectures, AI Agents, and modern AI patterns.
- Experience in Platform Engineering, DevOps, and cloud operations.
- CI/CD, Infrastructure as Code (Terraform, Bicep, CloudFormation), and automation expertise.
- 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.
Skills
- LangChain
- Semantic Kernel
- CrewAI
- AutoGen
- Vector databases
- AI orchestration frameworks
- Databricks
- Microsoft Fabric
- Enterprise data platforms
- MLOps
- ModelOps
- AIOps practices
Location
- Hybrid
Work Type
- Hybrid
Experience Level
- 5+ Years on DevOps & Platform Engineering
- 3+ Years on AI Ops
Education Level
- Azure AI Engineer Associate
- Azure DevOps Engineer Expert
- AWS AI Practitioner
- AWS Machine Learning Engineer / Specialty
- AWS DevOps Engineer Professional
- Kubernetes (CKA/CKAD)
Benefits
- Accredited Great Place to Work for Wellbeing in 2024
- Trained ‘Mental Health Champions’
- Wellbeing apps such as Thrive and Peppy
- Empowerment to explore, innovate, and progress
- Countless training and development opportunities
- Access to 250,000 courses
- Numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications and more
About the Company
- Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value.
- We imagine the future of organizations and make it real with AI, technology, and people.
- With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries.
- We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering, and business operations.
- The Group reported 2025 global revenues of €22.5 billion.
- Make it real | www.capgemini.com
Equal Opportunity
- Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme.
- As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who: Declare they have a disability, and Meet the minimum essential criteria for the role.
- Please opt in during the application process.