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. Put simply, we build software for the people who enable trust between businesses.
We’re based in San Francisco, CA, and built remote-first so you can do your best work from anywhere. We’re backed by top investors, including Growth Equity at Goldman Sachs Alternatives, Bessemer Venture Partners, 8VC, Floodgate, Y Combinator, DNX Ventures, Global Founders Capital, Justin Kan, Elad Gil, and more.
We value diversity—in backgrounds and experiences—and we want teammates from all walks of life to help build the future of audit and advisory. Our team is inclusive, driven, humble, and supportive. We’re intentional about the culture we’re building, and we look for people who are exceptional in their craft and committed to helping others grow.
As an early-stage startup employee, you’ll help shape the future of business trust. We make audit practitioners’ lives easier by consolidating up to 50% of their work and improving work-life balance. If you’re excited to build a great product and an even better culture, you’ll feel at home at Fieldguide.
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.
We’re backed by Goldman Sachs Alternatives, Bessemer Venture Partners, 8VC, Floodgate, Y Combinator, Elad Gil, and other top-tier investors.
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.
We’re hiring across levels and calibrate seniority during interviews based on your background and what you want to own. This role is for engineers who value in-person collaboration in our San Francisco, CA office.
Build agentic systems that automate and augment complex audit workflows
Turn customer problems into concrete agent behaviors and workflows
Orchestrate LLMs, tools, retrieval, and logic into reliable agent experiences
Own agents in production, including reliability, performance, and observability
Use AI to accelerate how you design, build, test, and iterate
Prototype quickly, then harden systems for enterprise-grade reliability
Build evaluations, feedback loops, and guardrails to improve agents over time
Design prompts, retrieval pipelines, and orchestration that perform at scale
Make clear trade-offs on what to build, cut, or skip
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 progress without waiting for direction
Take end-to-end ownership of meaningful product areas—not just narrow tasks
Increase team velocity with reusable abstractions, tools, and patterns
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
We care more about capability and trajectory than years on a resume, but most strong candidates have:
Several years shipping production software in complex, real-world systems
Experience with TypeScript, React, 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, etc.) and agent frameworks
Comfort operating in ambiguity and taking responsibility for outcomes
Empathy for professional-grade, mission-critical software (audit/accounting workflow experience not required)
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 transparent and trustworthy
Complex domains: Navigating compliance and enterprise rigor while moving fast
Shipping daily value: Delivering agent experiences customers use every day
Competitive compensation with equity
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.
Fearless — Inspire and break down seemingly impossible walls
Fast — Launch fast with excellence; iterate to perfection
Lovable — Deliver happiness and 11-star experiences
Owners — Execute and run the business with ownership
Win-win — Create mutual value and earn trust for life
Inclusive — Scale the best ideas with inclusive teams
Fieldguide automates and streamlines the work of assurance and audit practitioners, focusing on cybersecurity, privacy, and financial audit. By establishing a new state of trust in global commerce and capital markets, it empowers professionals in these critical fields to operate more efficiently and confidently.
Please mention you found this job on AI Jobs. It helps us get more startups to hire on our site. Thanks and good luck!
Understand the required skills and qualifications, anticipate the questions you may be asked, and study well-prepared answers using our sample responses.
AI Engineer Q&A's