AI Engineer Internship

About Solva

Solva is building AI for insurers to transform an $8 trillion industry, starting with claims. We’re backed by $6m from First Round, Y Combinator, SV Angel and angel investors, including Paul Graham, who have funded companies such as OpenAI, Google, Stripe, Anthropic, Databricks and Github. We have an advisory board of experienced insurance executives and founders.

Our team was previously part of building Europe’s fastest growing InsurTech and founded a licensed EU bank processing payments of €1B/yr+. Now we are taking on one of the world’s largest industries and rebuilding it from the ground up with AI.

Solva is a Y Combinator S25 company and has emerged as one of the fastest growing and best-funded startups.

About the role

As an AI Engineering Intern you will work closely with the founders and contribute to the core AI systems that power Solva. You will learn by working on real problems across reasoning, evaluation, data and model behavior, and help us improve how claims decisions are made. The work is hands on and fast moving.

You will experiment with models, build evaluation tools, refine agent workflows and work with challenging real world insurance data. This is a role for someone who is curious, enjoys solving technical problems and wants to work in a fast paced environment where ideas turn into product quickly.

Internship is full time. Start period can be discussed. Successful internships can lead to full time roles.

What you’ll do

• Work on the AI systems behind claims decision support and reasoning
• Work on agent workflows, evaluation pipelines, retrieval logic and prompt strategies
• Experiment with LLMs, fine tuning, RAG, embeddings and model selection
• Stress test outputs, break them, fix them and learn about engineering robust systems
• Ship fast, iterate with customers and turn messy problems into clean solutions
• Work on internal tools, dashboards and analysis frameworks that support our core product

What we’re looking for

• Strong interest in building with LLMs and working with real world data
• Someone who enjoys digging into complex problems, testing ideas and making things actually work
• Eagerness to own projects
• Not afraid of messy data, ambiguity or figuring things out from first principles
• Curiosity driven mindset, willing to read papers and try unconventional approaches
• Bonus if you have built your own AI projects, agents or research experiments
• Builder mentality. Move fast. Think clearly. Take ownership.