DevOps Engineer AI

CACEIS is the asset servicing banking group of Credit Agricole dedicated to asset managers and institutional investors. Through offices across Europe, North and South America and Asia, CACES offers a broad range of services covering execution, clearing, forex, securities lending, custody, depositary, fund administration, fund distribution support, middle-office outsourcing and issuer services. CACEIS is a consolidator in the European asset servicing market and posts sustained growth in its business activities. The group holds €5.3 trillion in assets under custody and €3.4 trillion in assets under administration (figures as of 31 December 2024) By working every day in the interest of society, we are a Group committed to diversity and inclusion and place people at the heart of all our transformations. All our job offers are open to people with disabilities. As part of IT Innovation projects, you will join the AI Factory/Innovation team as an AI DevOps Engineer. You will be responsible for designing, implementing and maintaining the infrastructures, CI/CD pipelines and environments required to deploy and operate AI solutions in production. You will work in agile mode, closely with AI developers, Data Scientists, Solution Architects and CACEIS infrastructure teams. You will play a key role in the industrialization of AI solutions and the automation of deployment processes. As an expert in vibe coding, you use generative AI tools (GitHub Copilot, Cursor, Claude, ChatGPT) to accelerate the creation of scripts, Infrastructure‑as‑Code configurations and CI/CD pipelines, and to quickly resolve production incidents. The assignment takes place in an English‑speaking environment; fluency in English is mandatory. Job Summary Design and implementation of Cloud architectures for AI solutions (scalable, secure, optimized) Deployment and management of Infrastructure as Code (Terraform, CloudFormation) Implementation of CI/CD pipelines for applications and AI models Expert use of vibe coding to generate scripts, configurations and automations Automation of deployments and rollbacks (blue/green, canary) Configuration of monitoring, alerting and observability for AI models in production Management of environments (dev, staging, production) and access controlOptimization of Cloud costs and performance (GPU, compute, storage)Support to developers on tooling and DevOps best practicesTechnical documentation of infrastructures and proceduresImplementation of DevSecOps practices and security complianceSharing of MLOps and vibe coding best practices with the team Experience At least 5 years of experience in DevOps/SREDemonstrated experience in vibe coding using AI tools to generate scripts, configurations and diagnose incidentsExpertise in MLOps and deployment of AI models in productionExperience in monitoring and observability (Prometheus, Grafana, ELK, DataDog)Knowledge of DevSecOps security practicesExperience with secrets and configuration management (Vault, AW, Secrets Manager)Nice to have: Experience with GPUs and optimization of AI resources Required skills Ability to use AI to quickly diagnose and resolve incidentsPragmatism: balance between automation and delivery timelinesRigour in designing and securing infrastructuresInnovative mindset and continuous technology watchAutonomy and proactivity in identifying issuesStrong service orientation and support for development teamsCollaborative and pedagogical mindsetHigh responsiveness when dealing with production incidents Technical skills required Proficiency with Cloud platforms (AWS, Azure, GCP) and Cloud AI servicesExpertise in Infrastructure as Code (Terraform, CloudFormation, ARM Templates)Strong skills in containerization and orchestration (Docker, Kubernetes, Helm)CI/CD expertise (GitLab CI, GitHub Actions, Jenkins, Azure DevOps)Knowledge of MLOps tools (MLflow, Kubeflow, Weights & Biases, SageMaker Pipelines)Proficiency in scripting (Bash, Python) and automation