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Job Description
Design, develop, and deploy enterprise AI agents and multi-agent solutions using Google's AI ecosystem. Leverage enterprise data, semantic models, and cloud services to deliver scalable, secure, and Responsible AI solutions.
Key Responsibilities
- Develop and deploy multi-agent solutions using Gemini and Agent Builder.
- Design and implement RAG (Retrieval-Augmented Generation) solutions leveraging EDW data and Looker semantic models.
- Integrate AI agents with enterprise APIs, databases, and Google Cloud Platform (GCP) services.
- Optimize agent performance, orchestration,



and user experience for business-critical use cases.
- Implement Responsible AI practices, including governance, security, monitoring, and compliance controls.

Technical Requirements
- Hands-on experience with Gemini, Vertex AI, and Agent Builder.
- Strong proficiency in Python, SQL, and API integration.
- Experience building AI Agents, Multi-Agent Systems, and RAG architectures.
- Knowledge of vector databases, embeddings, and semantic search.
- Experience with BigQuery, Cloud Run, Cloud Functions, and other GCP services.
- Familiarity with Looker, semantic layers, and enterprise data warehouse architectures.
- Experience with AI orchestration frameworks such as LangChain, LangGraph, or Google ADK.
- Understanding of Responsible AI, AI governance, security, and model evaluation.

Capgemini is a integral business and technology transformation partner, helping organizations to accelerate t

📌 Google Agentic AI Engineer (Bogotá, D.C.)
🏢 Capgemini Engineering
📍 Bogotá, D.C.