Data Engineer IA Rag.. - English & French - Based In Lyon Full-Time H/F

collectivite

Information importante

Type de contrat: Freelance

Taux journalier : Salaire selon profil

Localisation : Lyon, France

Date de démarrage :

Urgent

Mode de travail : Sur site

Publié le : 17 juin 2026

Le besoin

One requirement is to be based in Lyon or closed to Lyon. Please apply if you are concerned

Mission Description

In collaboration with the Data & AI team, you will be involved across the entire

lifecycle of AI solutions:

1. AI Solution Design and Development

- Estimate, design, and implement AI solutions, from POC phase to

industrialization.

- Leverage AI models via:

o generative model APIs (LLMs),

o Python AI libraries and frameworks (Scikit-learn, SpaCy,

LangChain, LangGraph...).

° Design and optimize prompts and AI pipelines.

- Implement RAG architectures.

- Connect AI solutions to data and the Groupe ecosystem (SQL,

tool calling, MCP).

- Write associated technical and functional documentation (interface

contracts, user guides, etc.).

2. Industrialization and Deployment (CI/CD & Cloud)

- Deploy AI APIs and workflows on AWS cloud (ECS, Lambda, etc.).

- Containerize solutions using Docker.

- Create simple testing and demo interfaces (Streamlit).

- Integrate solutions into CI/CD pipelines:

o automation of tests, builds, and deployments,

o use of tools such as Jenkins, GitHub Actions, Terraform.

- Manage access and ensure security, compliance, and data protection.

3. Operations, Performance, and Optimization

- Ensure operational stability of solutions: high availability, performance,

etc.

- Implement MLOps / monitoring practices and respond quickly to

incidents.

- Analyze technical performance and costs of deployed solutions.

- Provide recommendations to optimize architecture and cloud costs.

4. Collaborative Work & Knowledge Sharing

- Contribute to collective engineering practices:

o version control and code reviews via GitHub,

o design and sharing of common components, packages, or

frameworks.

- Support upskilling of internal teams: training and best practices.

- Maintain continuous technology watch on AI and GenAI

advancements.

Profil recherché

Python (advanced level): AI / GenAI frameworks and libraries:

LangChain, LangGraph, Scikit-learn, etc.

Prompt design and optimization.

Use of LLM APIs (Azure OpenAI, AWS Bedrock).

Design of RAG architectures and use of vector databases such as Qdrant

(embeddings, semantic search).

Knowledge of Model Context Protocol (MCP) and agent-based

architectures.

Containerization with Docker.

Deployment of solutions on AWS (ECS, Lambda, S3).

CI/CD: GitHub Actions, Jenkins, Infrastructure as Code (Terraform).

Understanding of MLOps / monitoring, performance, and cost

optimization.

Best practices for API security and access management.

Data handling via S3 and SQL databases.

Prototyping and demos using Streamlit.

4 days onsite per week