We're looking for an AI Developer to build the AI backbone of our product — retrieval-augmented generation pipelines, multi-step agent workflows, embedding systems, and LLM integrations that property managers rely on daily.

You’ll work directly with product and engineering to ship AI features end‑to‑end: designing vector search strategies, building agent loops, evaluating model quality, and shipping systems that actually work in production. You won’t just execute tickets — you’ll bring a point of view on embedding models, chunking strategies, reranking approaches, and the real tradeoffs between quality, latency, and cost.

Tasks

• RAG Pipelines: Design and build retrieval-augmented generation systems. Own chunking strategy, embedding selection, retrieval optimization, and reranking.
• Vector Databases: Implement and manage vector search infrastructure (Pinecone, Weaviate, or similar). Integrate embeddings with our MongoDB core data layer.