Description
Overview We're a growing B2B services company looking for an experienced AI Automation Engineer to design and build a production-grade AI assistant and workflow automation system. This is a real production build for a live business — not a prototype, not a demo. If your experience is limited to tutorials or chatbot demos, this isn't the right fit. What You'll Build 1. RAG-Powered Knowledge Assistant Build a Retrieval-Augmented Generation (RAG) pipeline over our internal knowledge base (PDFs, Word docs, Google Drive files, Notion pages) Document ingestion, chunking strategy, embeddings, and semantic search using a vector database (Pinecone or pgvector — recommend one and justify it) Grounded, hallucination-free answers with source citations — the bot must say "I don't know" when the answer isn't in the documents Multi-turn conversation memory and clean escalation to a human agent with full context Accessible via a web chat UI (React/Next.js) and WhatsApp Business API 2. AI Agent Layer with Tool Use LLM orchestration using LangChain or LangGraph (multi-step tool calling) Function calling / structured JSON outputs (Pydantic schema enforcement) for CRM updates, appointment booking (Calendly/Google Calendar), and lead qualification (Hot/Warm/Cold scoring) Human-in-the-loop approval workflow — no AI output touches a customer without review 3. Workflow Automation n8n (or Make.com) workflows connecting Gmail/Outlook, HubSpot CRM, Slack, Airtable, and Google Sheets Email triage: class