Senior AI Engineer

🔥 0 minutes ago

🇨🇴 Colombia – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

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Logo of Capgemini

Capgemini

10,000+ employees

Founded 1967

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Capgemini is a global leader in partnering with businesses to transform and manage their operations by harnessing the power of technology. With expertise across a wide array of industries such as aerospace, automotive, banking, and healthcare, Capgemini provides a constantly evolving portfolio of services to meet the ever-changing needs of their clients. Their offerings include cloud, cybersecurity, data and artificial intelligence, and enterprise management, among others. Capgemini also emphasizes innovation and sustainability, helping companies achieve digital transformation while promoting environmental and social responsibility. Additionally, Capgemini provides career opportunities across various levels and professions, encouraging innovation and diversity in its workforce.

📋 Description

• Design, develop, and deploy AI and GenAI solutions for business use cases • Build and optimize LLM-based applications, AI agents, and multi-agent systems • Develop RAG solutions using enterprise data sources and knowledge repositories • Integrate AI solutions with APIs, databases, business applications, and enterprise platforms • Evaluate, fine-tune, and monitor AI models to ensure performance, accuracy, and reliability • Implement Responsible AI, governance, security, and observability best practices • Collaborate with Data Engineers, Data Scientists, and Product teams to operationalize AI solutions

🎯 Requirements

• Strong proficiency in Python and API development • Experience building applications with Large Language Models (LLMs) and Generative AI technologies • Hands-on experience with AI Agents, Multi-Agent Systems, and RAG architectures • Knowledge of vector databases, embeddings, semantic search, and knowledge retrieval • Experience with AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, or similar • Familiarity with prompt engineering, model evaluation, and AI application monitoring • Understanding of software engineering best practices, including Git, CI/CD, testing, and cloud-native architectures • Knowledge of AI governance, security, privacy, and Responsible AI principles

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