Description
Summary We are building a suite of intelligent automation systems and need a seasoned AI engineer who has shipped real production systems, not just tinkered with tutorials. What You Will Be Working On You will design and deploy end-to-end AI agents capable of multi-step reasoning, tool use, and autonomous task execution. This includes building robust Retrieval-Augmented Generation pipelines with proper chunking strategies, embedding models, vector stores (Supabase, Pinecone, or Weaviate), and metadata filtering that actually works under load. You will also architect and maintain n8n workflow automation that connects these AI systems to external APIs, databases, and business logic without breaking every time an upstream service sneezes. Beyond that, you will handle LLM orchestration using frameworks like LangGraph or CrewAI, design context-aware memory systems, write clean async Python or TypeScript backends, and integrate everything into deployable services on platforms like Vercel, Railway, or AWS. You Are The Right Fit If You have built and deployed at least one production RAG system and can talk about what broke and how you fixed it. You understand the difference between naive chunking and semantic chunking and why it matters. You have wired up n8n or a comparable automation tool to real external services. You have worked with OpenAI, Anthropic, or open-source models and know when to use which. You write code that other engineers can read. Tech Stack You Should Know Python, FastAPI, LangChain or LangGraph, OpenAI or Anthropic APIs, Supabase or Pinecone, n8n, Docker, and at least one cloud platform. Bonus points for experience with voice agents, multimodal pipelines, or fine-tuning workflows. Show Us Your Work Share your GitHub profile, any public repositories relevant to AI agents or RAG systems, and links to live projects or demos if you have them. A portfolio page, a Notion showcase, a YouTube demo, anything that lets us see what you have actually built. We take work samples seriously and they will significantly strengthen your proposal. Engagement Details This is an ongoing contract with consistent hours. Hourly rate: $55 to $95 per hour depending on your experience level and the quality of your proposal. We pay well because we expect strong, independent contributors who do not need their hand held. One Last Thing If you actually read this post instead of firing off a copy-paste proposal, start your message with the words DingDong and then tell me about one RAG system you built and what the single hardest problem was. Also share your GitHub and any relevant portfolio links directly in your opening message. Proposals that do not follow this will be archived without review. Looking forward to hearing from the builders.