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LLM Agent Developer (LangChain / RAG / PDF/Notion Inputs Only – No APIs)
About Us: We’re a UK-based AI automation agency working with a fast-growing UK company that wants to build multiple internal/external AI agents to support operations across sales, strategy, marketing, invoicing, and more. We're kicking off a pilot project with 3–5 agents, things like: * Deck builder agent * Proposal generator agent * Invoice explainer agent * Strategy planner agent What You'll Be Doing: * Working with the Lead AI Architect to build AI agents using LangChain, LangGraph or other LLM frameworks * Implement RAG pipelines to inject context from PDFs, Notion pages, or spreadsheets * Write clean Python code to orchestrate logic, tools, and outputs * Use OpenAI (GPT-4 / GPT-4o) or similar models with function calling * Optionally build simple Streamlit apps or CLI tools to run/test the agents Must-Have Skills: * Proven experience building agents or copilots using **LangChain, LangGraph, or OpenAI Assistants API** * Strong Python skills * Experience with RAG setups: text chunking, vector DBs (FAISS, Chroma, etc.), and embedding models * Comfortable parsing documents: PDFs, CSVs, Notion exports, etc. * Able to work **without using APIs** to external tools (no CRM/email/calendar APIs) * Attention to detail in prompt crafting, function design, and LLM response control * Front-end skills --- Nice-to-Have: * Familiarity with tools like Unstructured.io, PyMuPDF, python-docx, etc. * Experience with LangSmith / Langfuse for observability Project Scope: * Initial project: Build and deliver 3 working agents (each with defined goal and input/output spec) * Timeline: \~4–6 weeks * If successful, we’ll expand to a longer-term collaboration to scale 30+ agents over time Time & Budget: * Looking for full-time fixed term (1-3 months), with option to be longer How to Apply: Please share: * A short intro on your experience with LLM agent development * Examples or GitHub links to past LangChain, RAG, or LLM projects * A note on how you'd approach building an agent that explains an invoice from a PDF