Senior 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. As a Senior AI Engineer, you'll own meaningful product areas end-to-end—designing agentic architectures, building evaluation systems, and shipping agents that professionals trust with mission-critical work. This role is for engineers who have shipped LLM-powered features in production and are ready to take the lead on complex systems while mentoring those around them. What You’ll Own Build and Ship AI Agents Design and build agentic systems that automate complex audit workflows end-to-end Translate customer problems into concrete agent behaviors and orchestration logic Orchestrate LLMs, tools, retrieval, and business logic into reliable, production-grade agent experiences Own agents across their lifecy [... source excerpt omitted ...] over time Design prompts, retrieval pipelines, and orchestration logic that perform at scale Drive Product Impact Make clear trade-offs on what to build, cut, or skip based on customer value Partner with Product and Design to define capabilities that deliver real outcomes Stay close to customer workflows and optimize for highest-impact problems Identify capability gaps and unblock team progress proactively Mentor and Multiply the Team Raise the quality bar through code review, design feedback, and pairing Create reusable abstractions, patterns, and tooling that increase team velocity Share learnings across the team and establish engineering best practices Who You Are [... source excerpt omitted ...] learn quickly from feedback and adjust based on data Grounded optimism: You improve what's broken today and push toward what's possible next End-to-end ownership: You understand production systems and own outcomes Experience We care more about capability and trajectory than years on a resume, but most strong candidates have: 3–6+ years shipping production software in complex, real-world systems Strong command of TypeScript, Python, and Postgres Shipped LLM-powered features serving real production traffic Built retrieval pipelines and agent orchestration systems Implemented evaluation frameworks for model outputs and agent behavior Worked with vector databases, embedding m