AI Engineer Needed for 7-Day AI Agent & RAG Build

We’re looking for an AI Engineer for a 7-day project to build and validate a production-oriented AI workflow for our SaaS platform. We already have an existing product, backend, APIs, and data sources. We need an engineer who can quickly understand the existing architecture and build a working AI capability that integrates with it. This is not a research project or a basic ChatGPT chatbot. The goal is to have a functional AI agent/RAG workflow that can be tested inside our existing system by the end of the engagement. What You’ll Build During the 7-day engagement, you’ll focus on one defined AI use case, which may include: • An AI agent that can interact with our APIs or internal tools • A RAG pipeline over our existing business data • An AI assistant that retrieves grounded information • LLM-powered analysis, summaries, or recommendations • An automated workflow connecting an LLM to existing systems • A backend API exposing the AI capability to our application Responsibilities • Review our existing APIs, database structure, and relevant data sources • Recommend the appropriate AI architecture for the use case • Build the initial agent/RAG workflow • Integrate an LLM such as OpenAI or Anthropic • Connect the AI system to relevant APIs, databases, or tools • Implement basic validation, error handling, and fallback logic • Test the workflow against representative use cases • Deploy the working implementation to our development/staging environment • Document the architecture, workflow, configuration, and next steps Preferred Stack Experience with several of the following: • Python • FastAPI • LangChain / LangGraph • RAG • AI Agents • OpenAI / Anthropic APIs • PostgreSQL / pgvector • REST APIs • n8n / Flowise / Langflow • Docker • AWS or DigitalOcean • Redis • MCP Ideal Candidate We’re looking for someone who has actually built AI systems rather than someone who only works with prompts or basic chatbot integrations. You should be comfortable moving quickly from: Requirement → Architecture → Implementation → Integration → Testing → Deployment You should also be able to make sensible technical decisions independently and communicate clearly when requirements or implementation details need clarification. To Apply Please include: 1. One AI agent, RAG system, or LLM application you’ve built. 2. One automation workflow you’ve built using n8n, Flowise, or a similar platform. 3. The technologies used in those projects. 4. A brief explanation of how you would approach our 7-day build. 5. A link to a relevant demo, GitHub repository, or case study if available. We’re looking for someone who can deliver a working implementation quickly and potentially continue with us for the production phase after the initial engagement.