Key Responsibilities

• Architect and implement production-grade Conversational AI products and systems
• Build and deploy conversational AI systems, chatbots, and LLM applications
• Work with AWS Bedrock, Azure OpenAI, Agentcore, or similar platforms
• Develop and manage MCP (Model Context Protocol) servers
• Design AI agent architectures and orchestration using LangChain, LangGraph, or LlamaIndex
• Build and deploy RAG (Retrieval Augmented Generation) systems in production environments
• Stay up to date with fast-moving AI trends, particularly in LLMs, conversational AI, and agentic systems
• Collaborate on large-scale data engineering tasks using PySpark, Apache Spark, or AWS EMR where needed

Requirements

• Proven experience building conversational AI systems, chatbots, and LLM applications
• Hands-on experience with AWS Bedrock, Azure OpenAI, Agentcore, or similar platforms
• Experience building and managing MCP servers
• Proficiency with LangChain, LangGraph, or LlamaIndex for AI agent architectures and orchestration
• Experience building or deploying RAG systems beyond tutorials in production environments
• Strong Python development skills
• Experience with AWS or Azure cloud platforms
• Architecting and implementing production-grade Conversational AI product experience is a must
• Nice to have: PySpark experience and experience with Apache Spark or AWS EMR
• Nice to have: Experience on SageMaker, SageMaker Pipelines, or SageMaker Notebooks

Skills Required