DevOps / MLOps Engineer

Jobtailor; Strasbourg; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Jobtailor in Strasbourg is seeking an experienced DevOps/MLOps engineer to operate, automate, and secure a production AI platform. You will design and evolve CI/CD pipelines for AI/GenAI workloads, and deploy containerized environments with Docker and Kubernetes.

You will implement orchestration workflows, integrate MLflow and Langfuse, and help establish AI governance, security, and observability across the production lifecycle.

Qualifications

• 4 to 7 years of experience in demanding DevOps/MLOps environments.
• Practical DevOps and MLOps practices applied to AI/GenAI environments.
• Cloud platform: Microsoft Azure (including Azure AI Foundry, Azure OpenAI, Entra ID, Key Vault).
• MLOps & tracking tools: MLflow, Langfuse.
• Orchestration & automation: n8n, Airflow or equivalent.
• Containerization & orchestration: Docker, Kubernetes.
• CI/CD, configuration management, secrets management and application security.
• Development and automation in Python.
• Experience with productionized AI or industrialized data platforms.

Responsabilités

• Operate, industrialize and secure the AI platform and its ecosystem.
• Implement and evolve AI- and MLOps-oriented CI/CD pipelines.
• Industrialize the lifecycle of models, agents and AI applications.
• Design and automate orchestration workflows (data & AI).
• Deploy and maintain containerized environments (Docker, Kubernetes).
• Integrate MLOps and observability tools into the production pipeline.
• Strengthen configuration and secrets management mechanisms.
• Contribute to establishing AI governance standards (security, compliance, auditability).
• Operate, maintain and evolve a production AI platform.
• Ensure monitoring, observability and traceability of AI workloads.
• Guarantee availability, performance and resilience of AI services.
• Manage incidents, rollbacks and operational maintenance.
• Support project and business teams in productionizing AI use cases.
• Continuously automate and improve DevOps/MLOps operations.
• Document architectures, pipelines and operational best practices.

Connaissances

Python development

DevOps

MLOps

AI/GenAI experience

Outils

Azure

Azure AI Foundry

Azure OpenAI

Entra ID

Key Vault

MLflow

Langfuse

n8n

Airflow

Docker

Kubernetes

Description du poste

Responsibilities

• You will be responsible for operating, industrializing and securing the AI platform and its ecosystem
• Implement and evolve AI- and MLOps-oriented CI/CD pipelines
• Industrialize the lifecycle of models, agents and AI applications
• Design and automate orchestration workflows (data & AI)
• Deploy and maintain containerized environments (Docker, Kubernetes)
• Integrate MLOps and observability tools into the production pipeline
• Strengthen configuration and secrets management mechanisms
• Contribute to establishing AI governance standards (security, compliance, auditability)
• Operate, maintain and evolve a production AI platform
• Ensure monitoring, observability and traceability of AI workloads
• Guarantee availability, performance and resilience of AI services
• Manage incidents, rollbacks and operational maintenance
• Support project and business teams in productionizing AI use cases
• Continuously automate and improve DevOps/MLOps operations
• Document architectures, pipelines and operational best practices

Qualifications

• 4 to 7 years of experience in demanding DevOps/MLOps environments
• Practical DevOps and MLOps practices applied to AI/GenAI environments
• Cloud platform: Microsoft Azure (including Azure AI Foundry, Azure OpenAI, Entra ID, Key Vault)
• MLOps & tracking tools: MLflow, Langfuse
• Orchestration & automation: n8n, Airflow or equivalent
• Containerization & orchestration: Docker, Kubernetes
• CI/CD, configuration management, secrets management and application security
• Development and automation in Python
• Experience with productionized AI or industrialized data platforms