Software Engineer

About the role

We 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.

What You’ll Get

• A high-impact role with ownership from day one.
• Competitive compensation and meaningful equity.
• Direct collaboration with founders and real users.
• Remote-first flexibility.
• The opportunity to help build an AI-native product from the ground up.

About The Role

We 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.

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.