Senior or Staff Software Engineer

Fieldguide; United States; On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Health

Dental

PTO

Job summary

Fieldguide is hiring a product-focused engineer to own an end-to-end agent area, shipping LLM-backed audit features to production and measuring their use by practitioners. You’ll work with PMs, designers, and domain experts to turn ambiguous problems into shipped protections and real artifacts.

Expect to build structured-output pipelines, conduct evals and error analysis, and set architectural tradeoffs for agent reliability and orchestration in a fast, collaborative, 0→1 environment.

Qualifications

• Experience with evals, error analysis and model-selection decisions.

Responsibilities

• Own a major agent area end-to-end, from agent reasoning to artifact review.
• Set evals and error-analysis practice for the team’s agent work.
• Collaborate with PMs and designers to shape roadmaps and define architectural tradeoffs.

Skills

Evals and error analysis

Product-minded

Full-stack development

Autonomy in ambiguous specs

Mentoring

Cross-functional collaboration

Tools

Python

TypeScript

React

PostgreSQL

Hasura

GraphQL

Langfuse / LangSmith / Arize Phoenix

Job description

• You’ll join a genuine 0→1 team on the ground floor of one of the company’s biggest new bets. This seat is specifically product-focused: you’ll own agent quality, ship agents 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
• Make agent judgment repeatable: run error analysis on real testing data and turn findings into concrete fixes
• Tradeoffs such as quality/latency/cost across a long multi-phase run
• Build structured-output pipelines that turn model output into real audit artifacts
• Take ambiguous problem statements and turn them into a plan, a shipped feature, and a clear read on what was cut and why
• Work directly with an embedded subject matter expert and with design-partner firms, turning their feedback into agent changes within days
• Expand agent coverage into new controls and new areas of internal audit
• Product-minded and full-stack: you’ve shipped LLM-backed features to production against real users, and you measure yourself on whether they got used
• You’re fluent in evals and error analysis, and you apply them in service of shipping something practitioners trust
• You have real opinions on model selection, prompting, and orchestration tradeoffs, and you can defend them with evidence rather than vibes
• Energized by 0→1 work: you’d rather define the problem than inherit a spec, and you don’t stall on ambiguity
• Strong instincts for human-in-the-loop design
• A genuine team player across the organization, not just within engineering: you’ll work daily with PM, design, domain experts, and customer-facing teams, and you treat that as the best part of the job
• Ship fast without leaving a mess: your code is reviewable, tested where it counts, and instrumented
• Able to internalize a hard domain fast. You don’t need to know SOX today, but you’ll understand it well enough to make the right product calls
• Own a major agent area end-to-end, from how the agent reasons about a class of controls through to the artifact a reviewer signs
• Set the evals and error-analysis practice for the team’s agent work, and decide what evidence justifies shipping a change or rolling it back
• Collaborate with PMs and designers to shape roadmaps and define architectural tradeoffs, including where the agent acts and where the auditor decides
• Own the harder model and orchestration judgment calls across a long multi-phase run
• Mentor other engineers and raise the bar on 0→1 execution and applied eval rigor
• Drive agent initiatives that reach beyond Internal Audit and influence how agents are built across Fieldguide
• Set and champion engineering standards for agent reliability, reproducibility, and defensibility
• Partner with engineering and product leadership to define long-term technical strategy for agentic audit work
• Serve as a trusted advisor to leaders across Engineering, Product, and Design
• Represent Fieldguide externally through writing, speaking, and open-source contributions

Benefits

• Health
• Dental
• PTO

Applied AI skillset: evals, error analysis, and model-selection decisions you owned and can explainShipped LLM-backed product features to production against real usersExperience working directly with customers, and comfort being in the room when they use what you builtComfortable full-stack, with enough backend depth to work in agent orchestrationA collaborative mode that works across PM, design, and domain expertsAutonomy working from an ambiguous specStructured-output work including schema contracts, generating real artifacts from model outputPython, TypeScript, React, Postgres, Hasura, GraphQLStartup experience, as a founder or as an early engineerHands-on eval experience (Langfuse, Braintrust, LangSmith, Arize Phoenix, or comparable)Temporal or comparable durable-execution / workflow orchestrationBackground in internal audit, SOX, accounting, or another regulated domainDocument processing, including PDF and Excel manipulation and annotationA 0→1 track record: things you started where no scaffolding existed