Software Engineer (Internal Audit, All Levels)

Fieldguide

United States

On-site

USD 180,000 - 260,000

Full time

9 days ago
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Benefits offered by this job

Health insurance
Dental coverage
Paid time off

Job summary

Fieldguide is building the next generation of agentic audit tooling from the ground up. You will own full-stack work on long-horizon agents, ship features that drive real audit outcomes, and collaborate with engineers, PMs, designers, and SOX subject-matter experts.

Senior and Staff tracks offer opportunities to set technical direction, lead complex programs, and influence cross-team architecture while delivering trustworthy, production-grade features.

Qualifications

  • Demonstrated ability to own end-to-end features from design to production.
  • Experience shipping LLM-backed features in production.

Responsibilities

  • Design and build agent-driven experiences for SOX control testing.
  • Own complex, end-to-end workstreams across the full stack.
  • Ship code from day one and ramp quickly into ownership of product areas.
  • Collaborate daily with product managers, designers, and subject matter experts.
  • Shape technical direction for agentic systems, AI tooling, and engineering best practices.
  • Mentor engineers and raise the technical bar across the team.

Skills

Full-stack engineering
Applied AI
0→1 delivery
Customer collaboration

Tools

TypeScript
React
GraphQL
Node.js
PostgreSQL
Python
Temporal

Job description

  • You’ll join a genuine 0→1 team on the ground floor of one of the company’s biggest new bets. You will work full-stack on long-horizon agents, ship features that do real audit work, and work alongside practitioners
  • Depending on your experience and what you’re looking to own, you may join building within a major agent area, owning one end-to-end, or setting technical direction for agentic audit work across the team. We’re hiring across all levels and will calibrate during interviews based on scope and demonstrated experience
  • Design and build agent-driven experiences for SOX control testing, deciding where autonomy makes sense and where the auditor stays in the loop
  • Own complex, end-to-end workstreams across the full stack
  • Make long agentic runs trustworthy: improve reliability, repeatability, performance, and observability so the same evidence produces the same defensible conclusion every time
  • Turn agent output into finished audit deliverables, including structured workpapers that adapt to whatever template a firm brings
  • Ship code from day one and ramp quickly into full ownership of significant product areas
  • Collaborate daily with product managers, designers, and SOX subject matter experts to work through difficult domain problems
  • Help shape technical direction and contribute to how the team thinks about agentic systems, AI tooling, and engineering best practices
  • At the Senior level, you may:
  • Lead complex projects or systems, setting technical direction and ensuring long-term health
  • Collaborate with PMs and designers to shape roadmaps and define architectural tradeoffs
  • Serve as a domain expert within one or more technical areas (e.g., agent orchestration, evaluation and quality, document processing, frontend architecture)
  • Mentor other engineers and help raise the technical bar across the team
  • At the Staff level, you may:
  • Drive company-level technical initiatives and influence cross-team architecture
  • Set and champion engineering standards for scalability, security, and performance
  • Partner with engineering and product leadership to define long-term technical strategy
  • Serve as a trusted advisor to leaders across Engineering, Product, and Design
  • Represent Fieldguide externally through writing, speaking, and open-source contributions
  • What Should Excite You:
  • 0→1 on the biggest bet: You’re building the agent and the product from scratch, on the ground floor of where the company is going
  • Real audit stakes: Your work directly affects what firms put in front of their clients, and what a reviewer is willing to sign
  • Customer proximity: Design-partner firms and an embedded SOX expert use what you ship within days of it landing
  • High trust, high autonomy: You’re given ambiguous problems and trusted to define the plan
Benefits
  • Health
  • Dental
  • PTO

You’ve built with LLMs in production, not just in prototypes. You know what breaks when real users and real documents hit an agentHigh degree of ownership; you don’t wait to be told what to doAble to pick up complex domain concepts quickly. You don’t need to know SOX or internal controls, but you’re the kind of person who can internalize it fastAlready using AI coding tools in your workflow and curious about where agentic approaches create real leverageA strong full-stack engineer who writes code every day and wants to continue doing soEnergized by 0→1 work: you’d rather define the problem than inherit a specComfortable in ambiguous, fast-moving environments where you figure things out as you goA genuine team player across the organization, not just within engineering. You’ll work directly with PM, design, domain experts, and customer-facing teams, and you treat that as the best part of the jobA collaborative mindset with an ability to work across PM, design, and domain expertsMust-have:Willingness to develop an Applied AI skillset including writing evals, using LLM observability tools, and being thoughtful about qualityComfortable full-stack, with enough backend depth to work in agent orchestrationShipped LLM-backed product features to production against real usersAutonomy working from an ambiguous specStartup experience, as a founder or as an early engineerA track record of 0→1 projects you took from nothing to something people useExperience working directly with customers, and comfort being in the room when they use what you builtFamiliarity with our stack: TypeScript, React, GraphQL, Node.js, PostgreSQL, Python, and TemporalExperience in internal audit, SOX, financial services, accounting, or complianceExperience with document processing, PDF/Excel manipulation, or evaluation frameworks for model output

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