Associate AI Engineer | Full Stack Developer | Financial Services - Atlanta Only

ABOUT BIP CAPITAL BIP Capital is an integrated private market investment platform built to create and capture opportunities through BIP Ventures traditional venture anchor funds, an Evergreen equity BDC, and private credit offerings. With a distinctive multi-stage, multi-sector investment approach and a growing array of capital offerings, BIP Capital has generated consistent top quartile returns since 2009. OUR PHILOSOPHY We are champions of our investors’ goals and stewards of founders’ dreams, but more than that, we are ethical, honest partners who serve, educate, and protect our founders and investors. We take on the challenges and complex conversations because we operate out of integrity and genuine care. ABOUT THE ROLE BIP Capital's technology team is hiring an Associate AI Engineer to help bring large language models into the day to day work of an investment platform. You'll work directly with a Senior AI Engineer to add AI capabilities to our existing full-stack applications, and to design and ship retrieval-augmented generation (RAG) systems, agentic workflows, and prompt-engineered LLM pipelines that real investment and operations teams rely on. This is an apprenticeship-style role built for someone early in their career who is a strong full-stack engineer first and genuinely curious about applied AI. You will not be expected to own architecture on day one. You will be expected to execute well, learn quickly, and take real work off the Senior AI Engineer's plate within your first few months Office Environment: Hybrid / On-site (In-office Wednesdays). What you'll do Add AI capabilities to our existing full-stack applications: new LLM-powered features, workflows, and interfaces built directly into the products our investment and operations teams already use. Build and improve RAG systems with a Senior AI Engineer, from chunking and embedding strategies through retrieval quality and evaluation. Manage context windows and model inputs: decide what information a model actually needs, how to structure it, and when a task calls for a different model or a multi-modal approach across text, documents, and images. Help design agentic workflows when the problem calls for it, including multi-step LLM pipelines, tool use, and orchestration. Prompt-engineer and evaluate LLM workflows, treating prompts and retrieval as things you measure rather than guess at. Write clean, testable services and data pipelines that move information reliably between systems. Translate fuzzy workflow needs from investment and operations colleagues into concrete technical problems. Requirements What we're looking for We weigh engineering fundamentals and trajectory far more heavily than years of experience or a specific pedigree. This is a product engineering role: we want a full-stack engineer who is genuinely excited about building with large language models, someone who thinks naturally in terms of retrieval, embeddings, context windows, and tool…