GenAI & Agentic AI Engineer — Remote (Mexico)

The Big Job Site; Aguascalientes; A distancia; MXN 900.000 - 1.500.000; Jornada completa

Descripción de la vacante

Capgemini is seeking an experienced GenAI engineer to design and deliver production-ready AI solutions across document processing and orchestration. You will build end-to-end pipelines that extract insights from unstructured documents using OCR and Document AI, and implement scalable LLM/RAG workflows.

The role requires hands-on development in Python, API integration, and cloud platforms (preferably GCP), with a focus on scalable, maintainable AI applications and strong English communication

Formación

• 5+ years building production-grade GenAI solutions.
• Strong OCR and Document AI expertise.
• Hands-on with AI agents, orchestration, and human-in-the-loop.
• Deep knowledge of LLMs and retrieval architectures.
• Strong Python and API development skills.
• Experience with cloud AI platforms (GCP/AWS/Azure).
• Fluent English.

Responsabilidades

• Design and deliver production-ready GenAI solutions from concept to deployment.
• Build Document AI and OCR solutions to extract insights from unstructured documents.
• Develop agentic AI workflows with agents, orchestration, and automation.
• Implement LLM and RAG architectures using embeddings, vector databases, and retrieval pipelines.
• Leverage Python, APIs, and cloud platforms to create scalable enterprise AI applications.

Conocimientos

GenAI architecture

OCR & Document AI

Agentic AI workflows

LLMs & RAG

Python & APIs

Cloud platforms (GCP/AWS/Azure)

English fluency

Herramientas

Embeddings & vectorDBs

Retrieval pipelines

Descripción del empleo

Capgemini is seeking an experienced GenAI engineer to design and deliver production-ready AI solutions across document processing and orchestration. You will build end-to-end pipelines that extract insights from unstructured documents using OCR and Document AI, and implement scalable LLM/RAG workflows.

The role requires hands-on development in Python, API integration, and cloud platforms (preferably GCP), with a focus on scalable, maintainable AI applications and strong English communication