Description

You will design, develop, and maintain AI-integrated applications using Python.

This role is hybrid.

Responsibilities

• Implement RAG pipelines integrating LLMs (OpenAI, Azure OpenAI, Hugging Face, LangChain, LlamaIndex) 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) and manage embeddings using vector databases (Pinecone, Weaviate, FAISS, Qdrant, Azure Cognitive Search).
• Optimize application performance, security, and scalability for production-grade AI systems.

Required Skills

• Minimum 8 years of IT experience, with 1+ years in AI.
• Strong hands-on experience with Python.
• Solid understanding of OOP, REST APIs, and microservices architecture.
• Proven experience with LLM-based applications and RAG integration.
• Practical implementation knowledge 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.

Preferred Skills

• Experience with Azure Cognitive Search.

Key Skills

Education

Any Graduate