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Generative AI Engineer / AI Enabler (TypeScript / RAG)

Original title: Ingénieur(e) IA Générative / AI Enabler (TypeScript / RAG) - H/F

Darwin Partners · Annecy, France · Hybrid · Senior

  • Annecy, France · Hybrid
  • French

Indexed (today) · refreshed constantly

Budget
€63–75 / h
Start
flexible
Work mode
Hybrid
Contract
Freelance / B2B
Seniority
Senior

Required skills

Languages: French

Job description

Join a new AI team at an international sports and outdoor brand to build reusable AI components and patterns for development teams. You will focus on RAG and AI Agent architectures, prompt engineering, and evaluation environments.

Project overview

Our client, a leading international brand in the sports and outdoor equipment sector, is deploying a new dedicated Artificial Intelligence team to industrialize AI engineering capabilities within its IT department.

This entity is structured into two poles: a "Platform" team (shared infrastructure) and an "Enablement" team (facilitation). The overall objective is to achieve measurable AI capability across the entire software development cycle within six months.

As part of this creation, you will join the Enablement team. Your role is to build the models (patterns), test environments, and reusable components that will support AI use cases. You will work directly on concrete projects alongside the development (delivery) teams. The artifacts you produce will feed a shared library, enabling other teams to build their own AI solutions autonomously.

Your missions

At the heart of creating value through AI, you will be responsible for the following areas:

  • RAG Architecture and Pipelines: Design and implement data retrieval strategies, chunking, re-ranking, and hybrid search. You will also contribute to architectural choices regarding storage and the vector layer.
  • AI Agent Architecture: Define tool usage patterns, multi-step reasoning flows, human-in-the-loop design, and context window management.
  • Prompt Engineering: Implement advanced prompt structuring techniques (few-shot design, chain-of-thought).
  • Evaluation Environments (Harnesses): Build the testing framework in close coordination with the LLMOps Engineer from the Platform team.
  • Shared Component Library: Develop reusable TypeScript components derived from use cases to feed the company's AI SDK.
  • Support and Co-construction: Participate in project kickoffs and the development of use cases hand-in-hand with product teams and deployment engineers.

Project details

  • Start: flexible
  • Remote: hybrid
  • Location: Annecy, France, FR
  • Rate: 63-75 EUR/h
  • Languages: French

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