Here is an Exciting Opportunity - Agentic AI - Capgemini

About the Role

We are seeking an exceptional Data Scientist with specialized expertise in developing multi-agent AI systems. In this role, you will design, implement, and optimize complex AI ecosystems where multiple intelligent agents collaborate to solve sophisticated problems. You will leverage your deep understanding of generative AI, retrieval-augmented generation (RAG), and prompt engineering to create cutting-edge solutions that push the boundaries of artificial intelligence.

Key Responsibilities

• Design and develop generative AI-based multi-agent systems that can collaborate, communicate, and coordinate to achieve complex objectives
• Architect and implement RAG-based chatbot solutions that effectively leverage knowledge bases and external data sources
• Create sophisticated prompt engineering strategies to optimize AI agent behavior and inter-agent communication
• Build, train, and fine-tune generative AI models for various applications within multi-agent systems
• Develop robust evaluation frameworks to measure and improve multi-agent system performance
• Implement efficient knowledge sharing mechanisms between AI agents
• Write clean, efficient, and well-documented Python code for production-ready AI systems
• Collaborate with cross-functional teams to integrate multi-agent systems into broader product ecosystems
• Stay at the forefront of AI research and incorporate state-of-the-art techniques into our solutions

Required Qualifications

• Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field
• 4+ years of professional experience in data science or machine learning engineering
• Extensive experience with Python programming and related data science/ML libraries
• Demonstrated expertise in developing and deploying generative AI models (e.g., LLMs, diffusion models)
• Proven experience building RAG-based systems and implementing vector databases
• Strong background in prompt engineering for large language models
• Experience designing and implementing generative AI-based multi-agent architectures
• Excellent problem-solving skills and ability to optimize complex AI systems

Preferred Qualifications

• Experience with LangChain, AutoGPT, CrewAI, or similar frameworks for building agent-based systems
• Familiarity with orchestration tools for managing complex AI workflows
• Knowledge of agent communication protocols and collaborative problem-solving frameworks
• Experience with distributed systems and cloud computing platforms (AWS, GCP, Azure)
• Contributions to open-source AI projects or research publications in relevant fields
• Experience with knowledge graphs and semantic reasoning systems