Description
We are looking for an experienced AI/ML Engineer to help us build a production- ready AI assistant for our customer support and internal operations team. We have a growing knowledge base made up of support tickets, PDFs, SOPs, website content, customer documents, and internal training material. We want to build an AI assistant that can answer questions accurately, provide source references, summarize customer issues, and help our team reduce manual work. This is not a simple ChatGPT wrapper. We need someone who has real experience building AI chatbots, RAG pipelines, LangChain workflows, vector search, API integrations, and production AI systems. What we need: Build a custom AI chatbot using LLMs and RAG Connect the chatbot with documents, PDFs, website content, and internal knowledge base Implement vector search using Pinecone, Chroma, FAISS, pgvector, or similar Add source citations and confidence handling for answers Build backend APIs using Python, FastAPI, or Django Create workflows for ticket summarization, document Q&A, and customer routing Add prompt templates, fallback logic, guardrails, and conversation history Deploy the system on AWS, Azure, or GCP Set up logging, monitoring, and basic performance tracking Optionally build a simple admin dashboard for uploads and knowledge base management Required skills: Python FastAPI or Django LangChain or LlamaIndex OpenAI API, Claude, Gemini, or similar LLMs RAG and vector databases NLP and doc