Level

Shepherd

Software Engineer, Applied AI

AI in this role

prompt-engineeringragai-agents

What We Do

Yesterday's insurance wasn't built for today's risk. We see it in the data and we feel it in the field. Emerging technology can reinvent how risk is priced and managed, faster and smarter, anchored in proven expertise. First-movers will define the next era of commercial risk management, and Shepherd is building it.

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.

Our Investors

In March 2026, Shepherd raised a $42M Series B — bringing total funding to over $60M — led by Intact Private Capital, the investment arm of one of the largest insurers in the world. Intact is not only our lead investor but also a carrier partner, a testament to the confidence the incumbent industry has in what we're building. Our investors:

Our Team

We're a team of technologists and insurance enthusiasts, bridging the two worlds together. Check out our About page to learn more.

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 into concrete AI systems

  • You have at least 5+ years of working experience (preferably as a full-stack engineer) with a track record of delivering high-impact products

Bonus Points

  • 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

Why This Role Matters

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.

Our Tech Stack

Frontend

  • React & Next.js

  • Typescript

  • GraphQL w/ Apollo

Backend

  • Node.js

  • Postgres & Redis

  • Typescript

  • GraphQL APIs

How we work

Shepherd runs on four values. Here's what each one means in this seat.

  • Think big, build big. We exist to protect progress and the industries that rely on it. The work here is aimed at a system that runs on its own, and the roadmap gets sequenced backward from that rather than forward from what's easy.

  • Win together. We rise as one. We support each other, raise the bar, and celebrate collective success. As the first PM you set a standard the rest of the team inherits, and the milestones belong to the team rather than to product.

  • Cross the aisle. Collaboration wins. We listen deeply, work across boundaries, and prioritize shared success over individual lanes. The best product calls here come from engineers who've sat with underwriters and underwriters who understand where the model breaks, and much of this job is listening closely enough on both sides to make that happen.

  • Go get it. We act with urgency, move with confidence, take smart risks, and push forward with intention. Nobody hands you the roadmap, the data, or the meeting invite. You pull the failing runs, book the time with the underwriters, and decide what matters.

Benefits 

🏥 Premium Healthcare
100% contribution to top-tier health, dental, and vision

🥕 Fertility benefits and family building support

🏖️ Unlimited PTO
Flexibility to take the time off, recharge, and perform

🥗 Daily lunches, dinners, and snacks
We work together, and enjoy meals together too

🖥️ SF, NYC, Dallas-Fort Worth, Chicago and LA Offices

📚 Professional Development
Access to premium coaching, including leadership development

🏦 Competitive 401(k) Plan

🐶 Dog-friendly office
Plenty of dogs to play with and make friends with in the SF office

How we score this

Software Engineer, Applied AI at Shepherd scores 65 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 3. The daily work is on or around AI systems, without necessarily building the model: remove AI and the job is hollow.

  1. AI Level 480 to 100
  2. AI Level 360 to 79
  3. AI Level 240 to 59
  4. AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringRagAI Agents

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How do you decide when an AI agent can act on its own versus asking for approval first?
  4. Describe a typical day in a role like this one: which parts run through AI directly?
  5. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering, Rag, and AI Agents. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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