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Your Role

As an AI / LLM Engineer at Capgemini, you will design, develop, and optimize advanced solutions based on Large Language Models (LLMs), focusing on retrieval-augmented generation (RAG) and intelligent search systems.

You will be responsible for implementing and enhancing chunking and embedding strategies for text and images, improving how data is indexed, retrieved, and consumed by AI systems.

This role requires strong experience in prompt engineering, hybrid search, re-ranking techniques, AI guardrails, and evaluation frameworks, ensuring high-quality, safe, and scalable AI solutions.

Responsibilities & Scope




- Design and implement chunking and embedding strategies for text and image data
- Develop and optimize prompt engineering techniques for LLM-based systems
- Implement hybrid search and re-ranking mechanisms to improve retrieval accuracy
- Enrich data chunks using metadata filtering and structuring techniques
- Build, test, and validate AI guardrails to ensure safety, quality, and compliance
- Perform AI client testing and evaluation to validate model outputs and performance
- Improve retrieval accuracy and response quality in RAG-based architectures
- Collaborate with AI/ML teams to optimize models and system performance
- Contribute to the design of scalable, high-performance AI retrieval systems

Your Profile

AI & LLM Expertise – Strong understanding of LLMs, NLP concepts, and RAG architectures, with the ability to design and optimize intelligent retrieval systems.

Prompt & Retrieval Optimization – Skilled in prompt engineering, embeddings, chu

📌 LLM Engineer (Aguascalientes)
🏢 Capgemini
📍 Aguascalientes