ABOUT THE ROLEWe are hiring a Software Engineer to build AI-powered features across our product and technical stack. You will work on real customer workflows, from AI and backend systems to product experiences, with strong support from a senior team.
WHY THIS ROLE- Build features that directly affect real customer workflows and outcomes.
- Work across a broad technical stack in an AI-native environment.
- Grow quickly with mentorship from founders and experienced engineers.
WHAT YOU'LL DO- Build product features powered by LLMs, including retrieval-augmented generation (RAG), embeddings and semantic search, prompt design, structured output, and tool-using agents.
- Work hands-on with the mechanics of AI systems: chunking and embedding documents, vector stores and retrieval, context construction, and evaluating output quality.
- Build the backend services, data pipelines, and product UI that turn these AI capabilities into reliable, production-grade features.
- Turn messy real-world insurance data into trustworthy, source-cited product capabilities.
- Collaborate across product, sales, and customer success to ship high-leverage work.
WHAT WE'RE LOOKING FOR- 1 to 3 years of software engineering experience (or equivalent), with strong fundamentals.
- Proficiency in Python and/or TypeScript and comfort with SQL.
- A real understanding of how modern AI systems work under the hood: LLMs and prompting, tokens and context windows, embeddings and vector search, RAG, and basic evaluation of model output.
- Genuine interest in applied AI and a desire to go deep on the domain.
- Strong ownership and comfort in a fast-moving environment.
BONUS IF YOU HAVE- Hands-on experience with LLM orchestration and RAG tooling (for example LangChain, LlamaIndex, or similar) and vector databases (for example pgvector, Pinecone, or Weaviate).
- Experience building agents, tool/function calling, or evaluation and prompt-testing pipelines.
- Experience with React, Postgres, or cloud platforms, or with document-heavy data.
