Associate Principal

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.