AI Engineer

About Us Fieldguide is establishing a new state of trust for global commerce and capital markets by automating and streamlining the work of assurance and audit practitioners—specifically in cybersecurity, privacy, and financial audits. We build software for the people who enable trust between businesses. We're based in San Francisco, CA, and built remote-first. We're backed by Goldman Sachs Alternatives, Bessemer Venture Partners, 8VC, Floodgate, Y Combinator, and more. Over 50 of the top 100 accounting and consulting firms trust Fieldguide to power mission-critical work. About the Role Fieldguide is building AI agents for the most complex audit and advisory workflows. We’re a San Francisco-based vertical AI company operating in a $100B+ market undergoing rapid transformation. Over 50 of the top 100 accounting and consulting firms trust Fieldguide to power mission-critical work. As an AI Engineer, you’ll build Fieldguide’s intelligence layer—agentic workflows, architectures, and evaluation systems that power enterprise-grade agents. You’ll operate at the intersection of product engineering, applied AI, and production systems. What You’ll Own Build and Ship AI Agents Implement agentic workflows that automate complex audit tasks Turn customer problems into discrete, testable agent behaviors Integrate LLMs, tools, and retrieval logic into reliable agent experiences Moni [... source excerpt omitted ...] Write prompts and retrieval pipelines that perform at scale Contribute to Product Impact Work closely with senior engineers and product to scope and deliver features Translate customer workflows into clear engineering requirements Identify and surface capability gaps to improve team velocity Who You Are You’re a strong software engineer who’s built your skills for an AI-native world. These principles resonate with you: Bias to building: You move fast and resolve uncertainty by shipping AI-native instincts: You're excited to use LLMs, agents, and automation as core tools Curiosity and learning velocity: You ramp quickly on new problems and technology Collaborative: You [... source excerpt omitted ...] quality in code and customer-facing outputs Experience We care more about capability and trajectory than years on a resume, but most strong candidates have: 1–3 years shipping production software in real-world systems Proficiency in TypeScript and/or Python Some exposure to LLM APIs (OpenAI, Anthropic, Gemini) or AI tooling Familiarity with retrieval pipelines, RAG concepts, or vector databases is a plus Experience with React and Postgres is helpful but not required Comfortable working in ambiguity with direction from senior engineers What Should Excite You Enterprise-grade reliability: Building systems professionals depend on Human-in-the-loop design: Knowing when to a