Software Engineer, Applied AI at Shepherd in San Francisco, CA

  • Company: Shepherd
  • Location: San Francisco
  • Job type: full time
  • Workplace: onsite
  • Posted: 2026-02-24

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Job description

What we do Build the insurance behind the physical world. The world is building data centers, energy projects, hospitals, schools, and critical infrastructure. Every one of those projects needs insurance to move forward. Yet the process of getting that insurance still depends on scattered documents, manual work, and weeks of back-and-forth. Shepherd is rebuilding commercial insurance with software, data, AI, and deep underwriting expertise. We started in construction and energy, where understanding the specifics of a project matters and better decisions have consequences far beyond a screen. We develop insurance products, decide which risks to insure and how to price them, and partner with established insurers to back the coverage. We own the platform our team uses to turn complex submissions into coverage for the builders and operators shaping the world around us. Real problems. Real ownership. Our engineers, designers, underwriters, and actuaries build together. The problems span turning messy documents into reliable data, making pricing more precise, and designing AI agents that can take on increasingly complex underwriting work. The ambition is a platform where experts spend more time on judgment and relationships, supported by software that handles the work around them. Join us to build systems whose decisions help real projects get built. 630+ customers / $500B+ insured project value Our investors Capital to build. Partners to grow with. $67M total funding / $42M Series B in March 2026 Shepherd is backed by Intact Private Capital, Costanoa Ventures, Spark Capital, Susa Ventures, and Y Combinator. In March 2026, we announced a $42M Series B led by Intact Private Capital, bringing our total funding to $67M. Intact is also a capacity partner. Alongside its investment, Intact works with Shepherd to bring insurance products to market. That relationship connects our platform and underwriting expertise with the resources of a global insurer. A bigger opportunity ahead We are investing in new insurance products, our underwriting team, and the path toward autonomous underwriting. For the people joining Shepherd, that means the chance to shape both the technology and the business it makes possible. Our backing brings together investors who build technology companies and partners who understand insurance. We are building a company that earns the confidence of both. The Role 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. What You’ll Do • 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 What We’re Looking For • 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 i

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