Fieldguide

Compensation

Full Description

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 building in a $100B+ market undergoing rapid transformation. Over 50 of the top 100 accounting and consulting firms trust us to power their most mission-critical work. We're backed by Bessemer Venture Partners, 8VC, Floodgate, Y Combinator, Elad Gil, and other top-tier investors. As an AI Engineer, you'll design and build the intelligence layer of Fieldguide, the agentic workflows, architectures, and evaluation systems that power enterprise-grade agents. This role sits at the intersection of product engineering, applied AI, and production systems. We're hiring across all levels. We'll calibrate seniority during interviews based on your background and what you're looking to own. This role is for engineers who value in-person collaboration at our San Francisco, CA office. What You'll Own Building and shipping AI agents Design, build, and ship agentic systems that automate and augment complex audit workflows Translate customer problems into concrete agent behaviors and workflows Integrate and orchestrate LLMs, tools, retrieval systems, and logic into cohesive, reliable agent experiences Own agents in production, including performance and observability AI-native engineering execution Use AI as core leverage in how you design, build, test, and iterate Prototype quickly to resolve uncertainty, then harden systems for enterprise-grade reliability Build evaluations, feedback mechanisms, and guardrails so agents improve over time Design prompts, retrieval pipelines, and agent orchestration systems that perform reliably at scale Product judgment and customer impact Make tradeoffs about what to build, what to cut, and what not to build at all Partner closely with Product and Design to define agent capabilities that drive real customer outcomes Stay deeply connected to how customers actually use agents and optimize for the highest impact problems Identify the highest-leverage capability gaps and unblock them without waiting for direction Ownership of large product areas Take full ownership of large product areas rather than executing on narrow tasks Identify bottlenecks and unblock progress without waiting for direction Increase team velocity by building reusable abstractions, tools, and patterns for agent development Who You Are You are a strong software engineer who has built your skills for an AI-native world. The following operating principles should resonate with you: Bias to building: You move fast and resolve uncertainty by shipping software AI-native instincts: You treat LLMs, agents, and automation as fundamental building blocks and parts of the craft of engineering Strong product judgment: You can decide what matters and why, without waiting for guidance, not just how to implement it Learning velocity: You move fast, learn from feedback, and adjust based on data Grounded optimism: You improve what is broken today and are energized by what becomes possible next End-to-end thinker: You understand how systems behave in production and own outcomes Experience We care more about capability and trajectory than years on a resume, but most strong candidates will have: Multiple years of experience shipping production software in complex, real-world systems Experience with TypeScript, React, Python, and Postgres Built and deployed LLM-powered features serving production traffic Designed retrieval pipelines and agent orchestration systems Implemented evaluation frameworks for model outputs and agent behaviors Worked with vector databases, embedding models, and RAG architectures Hands-on experience with modern LLM APIs (OpenAI, Gemini, Anthropic, etc.) and agent frameworks Comfort operating in ambiguity and taking responsibility for outcomes Deep empathy for professional-grade, mission-critical software (experience with audit and accounting workflows are not required) What Should Excite You Agent reliability at enterprise scale: Building systems that professionals depend on Balancing automation with human oversight: Knowing when to automate and when to surface decisions to experts Building evaluation systems when ground truth is nuanced: Audits require judgment, so structuring data in ways to get feedback is essential Explaining AI decisions: Making all forms of AI outputs and agent reasoning transparent and trustworthy Operating in a complex industry: Understanding compliance constraints and enterprise rigor while also moving fast Applied engineering where you ship agent experiences customers depend on daily Benefits Competitive compensation packages with equity ownership Comprehensive health and wellness benefits Flexible time off and work schedules Technology reimbursements 401(k) plan Twice-yearly in-person offsites across the U.S. Our Values Fearless — Inspire & break down seemingly impossible walls Fast — Launch fast with excellence; iterate to perfection Lovable — Deliver happiness & 11-star experiences Owners — Execute & run the business with ownership Win-win — Create mutual value & earn trust for life Inclusive — Scale the best ideas with inclusive teams