Senior AI Engineer: Agent Deployment & Production

Decathlon Digital EN

Paris, Paris, France

Hybrid

EUR 90,000 - 130,000

Full time

10 days ago

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Benefits offered by this job

Remote-friendly: 2 days/week
Training & skill upgrading
Internal/external training courses
Shareholders

Job summary

Decathlon Digital EN is seeking a Senior AI Engineer based in Paris to lead the deployment, monitoring, and orchestration of AI agents within our supply chain platform. You will design scalable deployment infrastructure, integrate SDKs, and ensure secure, cost-efficient operation across production environments, collaborating with data, product, and engineering teams.

The role emphasizes production-grade Python development, containerized deployments with Docker/Kubernetes, and building robust

Qualifications

  • Senior ML Engineer with production infrastructure release focus.
  • Experience with Vertex AI, MCP, and model routing.
  • Experience in deployment on GCP and containerized environments.
  • Ability to debug distributed architectures and custom connectors.

Responsibilities

  • Design and deploy AI agent hosting and production release foundations.
  • Build asynchronous multi-step pipelines with resilience.
  • Integrate agent orchestration SDKs (Vertex AI/ADK).
  • Optimize routing of tasks to appropriate models and control costs.
  • Ensure data security and proper access controls for agents.
  • Develop end-to-end tracing of agent decisions.

Skills

Python back-end
Docker
Kubernetes
CI/CD
LLMs
Model deployment
Distributed systems
Security & data access
GCP
Vertex AI

Tools

Databricks
MLFlow
Vertex AI Agent Builder

Job description

Decathlon Digital EN is seeking a Senior AI Engineer based in Paris to lead the deployment, monitoring, and orchestration of AI agents within our supply chain platform. You will design scalable deployment infrastructure, integrate SDKs, and ensure secure, cost-efficient operation across production environments, collaborating with data, product, and engineering teams.

The role emphasizes production-grade Python development, containerized deployments with Docker/Kubernetes, and building robust

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