Software Engineer, Applied AI

Partner with product, engineering, underwriting, and data teams to identify high-leverage AI opportunities

Design, build, and deploy LLM-powered features across underwriting, pricing, and internal tooling

Develop AI agents and retrieval-augmented systems that extract structured insights from unstructured insurance data

Build production-grade AI infrastructure for model serving, inference, evaluation, and monitoring

Create internal AI tools that enable underwriters and operators to move faster with higher quality decisions

Establish best practices for prompt engineering, evaluation frameworks, and model reliability

Own AI features end-to-end from ideation to production

Strong backend engineering experience building scalable APIs and distributed systems

Hands-on experience shipping AI-powered products into production

Familiarity with LLMs, RAG architectures, embeddings, and vector databases

Experience integrating AI systems into user-facing or workflow-driven applications

Comfort with cloud infrastructure and deploying AI workloads at scale

A product mindset and the ability to translate ambiguous business problems into concrete AI systems

Experience building AI agents or multi-step reasoning systems

Background in applied machine learning beyond generative AI

Experience with pricing systems, financial infrastructure, or risk modeling

Interest in transforming legacy industries with modern AI systems

Insurance is one of the largest industries in the world, yet much of underwriting and pricing remains manual and fragmented. At Shepherd, AI is not a side project – it is core to how we build durable competitive advantage.

You will help define how applied AI transforms risk evaluation in high-hazard industries and shape the future of AI-native insurance infrastructure.

Frontend

React & Next.js

Typescript

GraphQL w/ Apollo

Backend

Node.js

Postgres & Redis

GraphQL APIs