Fieldguide’s Total Rewards philosophy is to ensure holistic and competitive compensation that not only attracts and retains top talent but also fosters a culture of accountability and ownership in all the regions where we operate. Our salary ranges are determined by role, level, and location tier to ensure pay aligns with local market conditions and ensures fairness, transparency, and the recognition of employees' contributions. Job compensation ranges may span multiple career levels. The actual base pay for the successful candidate will depend on several factors, including location tier, transferable or job-related skills, work experience, relevant training/certifications, business needs, and market demands. Salary ranges are subject to change and may be adjusted in the future.

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

Compensation Range: $170K - $310K