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 lifecycle: delivery, reliability, performance, and observability

Execute with AI-Native Leverage

Use AI to accelerate design, build, test, and iteration cycles

Prototype quickly, then harden systems for enterprise-grade reliability

Build evaluation frameworks, feedback loops, and guardrails to improve agents 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

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 treat LLMs, agents, and automation as core building blocks

Strong product judgment: You decide what matters and why—not just how to implement it

Learning velocity: You 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 models, and RAG architectures

Hands-on experience with modern LLM APIs (OpenAI, Gemini, Anthropic) and agent frameworks

Comfortable operating in ambiguity and taking responsibility for outcomes

What Should Excite You

Enterprise-grade reliability: Building systems professionals depend on

Human-in-the-loop design: Knowing when to automate vs. when to surface decisions

Nuanced evaluation: Audits require judgment, so feedback structures matter

Explainability: Making AI outputs and reasoning tra