AI cloud DevOps & platform engineer

We are seeking a highly skilled AI Cloud DevOps & Platform Engineer who is responsible for the deployment, operation and continuous optimisation of AI, Machine Learning and Generative AI solutions across AWS and Azure. Combining AIOps, Platform Engineering and DevOps capabilities, the role ensures AI platforms are secure, scalable, resilient and production ready.

• 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 operationalise AI solutions.
• Contribute to AI platform strategy, standardisation and adoption of best practices.

• 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
• Будет плюсом: LangChain, Semantic Kernel, CrewAI or AutoGen; Vector databases and AI orchestration frameworks; Databricks, Microsoft Fabric or enterprise data platforms; MLOps, ModelOps and AIOps practices; Experience in regulated or large-scale enterprise environments; Consulting experience delivering cloud, platform or AI transformation initiatives; Azure AI Engineer Associate; Azure DevOps Engineer Expert; AWS AI Practitioner; AWS Machine Learning Engineer / Specialty; AWS DevOps Engineer Professional; Kubernetes (CKA/CKAD)

• The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
• You’d be joining an accredited Great Place to work for Wellbeing in 2024.
• To help support wellbeing we have trained ‘Mental Health Champions’ across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.
• You will be empowered to explore, innovate, and progress.
• You will benefit from Capgemini’s ‘learning for life’ mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications and much more.