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# Technical Lead

- **Company:** HCLTech France
- **Location:** Aix-en-Provence, France
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Software Quality, Continuous Integration, Python (Programming Language), Retrieval-Augmented Generation, Multi-Agent Systems, IT Architecture, Generative AI, CrewAI, AutoGen, Machine Learning Operations, Semantic Kernel
- **Published:** October 7, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=83d9dbbd152aaed0

## About the Role

Technical skills (must have)

 * Strong hands-on experience deploying production-ready Generative AI solutions.
 * LLM-based applications and RAG pipelines.
 * Architecting multi-agent systems with current frameworks, such as LangGraph, CrewAI, AutoGen or Semantic Kernel.
 * Cloud deployment on Azure, AWS or GCP.
 * MLOps and LLMOps: CI/CD, monitoring and model lifecycle.
 * Excellent Python programming.

Nice to have

 * Fine-tuning foundation models.
 * Experience with AI adoption and change management.
 * AI use cases in engineering, design or construction.
 * Experience guiding or coordinating a small team.

Other Requirements

 * Fluent English, written and spoken.
 * Based in Europe, with the right to work in the EU and the ability to be onsite a few days per week.
 * French is a plus.

## Description

* Integrate AI solutions with the client's existing IT tools and platforms.
 * Set up AI development practices that cover code quality, security and compliance.
 * Turn business needs into AI architecture and a delivery roadmap.
 * Support AI adoption from discovery to deployment, and help grow AI literacy across teams.
 * Work in agile delivery with client IT and engineering teams., * Design, develop and deploy GenAI and LLM applications in production across several business domains.
 * Build RAG pipelines and multi-agent systems.
 * Integrate AI solutions with the client's existing IT tools and platforms.
 * Set up AI development practices that cover code quality, security and compliance.
 * Turn business needs into AI architecture and a delivery roadmap.
 * Support AI adoption from discovery to deployment, and help grow AI literacy across teams.
 * Work in agile delivery with client IT and engineering teams.