Hearo is building an AI platform that turns public internet conversations (Reddit, app reviews, online communities) into structured product intelligence. The goal is to help founders and product teams understand what users actually think about products by analyzing discussions at scale.
We’re looking for a founding engineer to help build the first version of the platform.
The core technical work involves ingesting large volumes of public conversation data, building reliable async data pipelines, and implementing retrieval-augmented generation (RAG) systems that transform noisy discussions into useful insights like product pain points, feature requests, sentiment trends, and competitor signals.
Tech stack is flexible but will likely involve Python or Node.js, Postgres, vector search (pgvector/Pinecone), and LLM APIs (OpenAI/Anthropic). Experience with backend systems, APIs, scraping, or data pipelines is especially valuable. Experience building LLM or RAG systems is a strong plus.
We’re looking for someone who enjoys early-stage product building and is comfortable owning systems end-to-end.
Turning Reddit noise into structured product signals is exactly the kind of pipeline problem where RAG architecture matters — naive semantic search on raw posts misses context that entity-aware retrieval catches.
Relevant: GraphRAG demo — hybrid BM25+RRF retrieval on unstructured text, NetworkX entity graph, Claude for extraction, pgvector for embeddings. Built specifically to handle noisy real-world text. GitHub: github.com/ChunkyTortoise/graphrag-demo. Also: DocExtract AI (production, live) — async document pipeline, pgvector + Claude + ARQ worker, 234 tests. docextract-api.onrender.com
Stack match: Python, PostgreSQL, pgvector, RAG, LLM APIs (Anthropic/OpenAI) — every item in your stack is something I ship with. Available within 1 week.
This is right in my wheelhouse. I build RAG systems and LLM-powered data pipelines - ingestion, embedding, retrieval, and structured output generation. Python and Node.js, PostgreSQL with pgvector, OpenAI/Anthropic APIs.
Have built end-to-end async pipelines that process unstructured text into structured insights. Comfortable owning the full stack from scraping/ingestion through to the API layer.
Available for remote work. Happy to discuss further.
Apply: https://yourhearo.netlify.app/
Hearo is building an AI platform that turns public internet conversations (Reddit, app reviews, online communities) into structured product intelligence. The goal is to help founders and product teams understand what users actually think about products by analyzing discussions at scale.
We’re looking for a founding engineer to help build the first version of the platform.
The core technical work involves ingesting large volumes of public conversation data, building reliable async data pipelines, and implementing retrieval-augmented generation (RAG) systems that transform noisy discussions into useful insights like product pain points, feature requests, sentiment trends, and competitor signals.
Tech stack is flexible but will likely involve Python or Node.js, Postgres, vector search (pgvector/Pinecone), and LLM APIs (OpenAI/Anthropic). Experience with backend systems, APIs, scraping, or data pipelines is especially valuable. Experience building LLM or RAG systems is a strong plus.
We’re looking for someone who enjoys early-stage product building and is comfortable owning systems end-to-end.
If this sounds interesting, apply here: https://yourhearo.netlify.app/