Python Ai Developer

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 9 years of IT experience with 2+ 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.