Software Engineer, Applied AI

Shepherd•San Francisco, CA

22h

About The Position

Shepherd is a technology-driven Managing General Underwriter (MGU) transforming commercial Property & Casualty insurance for high-hazard industries. Our mission is to make risk frictionless for the builders and operators shaping the physical world — protecting progress from concept through construction and into decades of operation. We’re building the fastest, smartest commercial risk platform, where underwriting expertise, data, and automation work together to deliver: Faster decisions Smarter, more accurate pricing Better risk outcomes With Shepherd, safety, speed, and quality no longer trade off against one another — they compound. We’re not just modernizing insurance products. We’re building the risk infrastructure for the next generation of financial services, where technology, underwriting, and partnerships operate in harmony to support the world’s most important industries — and the progress they make possible. We are hiring a Software Engineer focused on Applied AI to build intelligent systems that directly power our underwriting and pricing engine. This role sits at the intersection of product engineering, AI infrastructure, and real-world insurance workflows. You will design and ship production AI systems that meaningfully improve how we evaluate risk, price policies, and operate our business.

Requirements

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

Nice To Haves

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

Responsibilities

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