Job Description Overview: I am looking for an experienced AI Automation Engineer to build a custom multi-agent email workflow. The system needs to handle client-specific requests via email, process data based on individual client contexts, and pass through a centralized QA agent before returning the final output. The Workflow: Client-Specific Agents: A dedicated AI agent (or dynamic context routing) for each client. When an email is sent with a thread, text, or file, the agent must use specific client knowledge (RAG/Knowledge Base) to update files or answer queries. Centralized QA Agent: Once the primary agent completes the task, the output must be automatically routed to a "QA Agent." This agent is uniform for all clients and is responsible for: - Fact-checking (preventing hallucinations). - Formatting and design consistency. - Verifying placeholders and client names. Email Integration: The entire interaction must happen via email (Inbound - Processing - Outbound). Technical Requirements: - Experience with LangChain or LangGraph for multi-agent orchestration. - Expertise in RAG (Retrieval-Augmented Generation) for managing separate client knowledge bases. - Proficiency in automation tools like Make.com, n8n, or custom Python scripts (AWS Lambda/Google Cloud Functions). - Experience with Email APIs (Postmark, SendGrid, or Gmail/Outlook API). Deliverables: - A scalable system where I can easily add new clients. - Secure handling of client-specific data. - A functional "Human-in-the-loop" option (optional but preferred).