Posted:1 day ago|
Platform:
Work from Office
Full Time
We are seeking a highly skilled Python Developer with expertise in Artificial Intelligence, Retrieval-Augmented Generation (RAG) integration, and Model Context Protocol (MCP). The candidate will be responsible for developing scalable applications, building intelligent search and conversational systems, and enabling seamless interaction between enterprise systems and LLMs using RAG + MCP pipelines.
Key Responsibilities:
• Design, develop, and maintain applications in Python.• Implement RAG pipelines by integrating LLMs (OpenAI, Azure OpenAI, Hugging Face, LangChain, LlamaIndex, etc.) with enterprise and external data sources.• Develop MCP-based integrations to connect tools, APIs, and enterprise data systems with LLMs.• Build APIs and microservices for AI-powered search, summarization, and conversational AI.• Create document ingestion pipelines (PDFs, databases, SharePoint, etc.) and manage embeddings with vector databases (Pinecone, Weaviate, FAISS, Qdrant, Azure Cognitive Search, etc.).• Collaborate with AI engineers, architects, and data teams to ensure scalable deployment of RAG/MCP solutions.• Optimize application performance, security, and scalability for production-grade AI systems.• Stay updated with AI frameworks, MCP standards, and cloud AI services.
Required Skills & Experience:
• Minimum of 8 years of IT experience with 1+ years of AI experience• Strong hands-on experience in Python.• Solid understanding of OOP, REST APIs, and microservices architecture.• Proven experience with LLM-based applications and RAG (Retrieval-Augmented Generation) integration.• Knowledge and practical implementation of Model Context Protocol (MCP) for AI tool orchestration.• Familiarity with vector databases (FAISS, Pinecone, Weaviate, Qdrant, Azure Cognitive Search).• Hands-on experience with LangChain, LlamaIndex, Hugging Face Transformers, or similar AI libraries.• Strong problem-solving and cross-functional collaboration skills.
Good to Have:
• Experience with containerization (Docker, Kubernetes).• Experience with cloud AI services (Azure, AWS, GCP) for deployment and scaling.• Exposure to SQL/NoSQL databases for structured and unstructured data.• Prior experience in chatbot development, enterprise search, or knowledge management systems.• Understanding of MLOps practices for AI model deployment and monitoring.
Capgemini
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