Who Gets Hired and Onto Which Teams
Fieldguide's agentic AI, as Fieldguide's product page reports, now runs audit procedures for eight of the top ten accounting firms — KPMG, RSM, Baker Tilly, BDO, Grant Thornton, and more than half of the top 100, and the startup's 35 open roles, as Zero G Talent's board data shows, reveal exactly who gets hired to build the next layer. This guide maps who Fieldguide hires, what they earn, how the interview loop works, where the team operates, and which traits predict success, drawn from the company's live job board and its product architecture.
The company sits at an unusual intersection: it sells agentic AI to the firms that define the profession, but it builds that AI with people who understand the work from the inside. The hiring question isn't whether you can write model code or close a deal. It's whether you can operate in the space where professional judgment meets production-grade agents.
Fieldguide's engineering organization splits across four tracks that map directly to its product architecture. The AI track owns the model layer. The Staff AI Engineer role posted on the Zero G Talent board signals a team building and tuning the agents that execute engagement procedures end to end. The AgentOps track treats those agents as operational infrastructure: the Software Engineer, AgentOps role focuses on observability, evaluation, and the feedback loops that keep agent error rates, as Fieldguide's product page found, below 1 percent. Infrastructure and Security round out the platform side; Staff Infrastructure Engineer and Lead Security Engineer postings show a team hardening the multi-tenant environment that feeds live engagement data into Claude, Copilot, and Gemini through the Model Context Protocol.
On the go-to-market side, the Strategic Account Partner / Client Transformation role reveals the actual motion. This isn't traditional enterprise sales. The title pairs "strategic account" with "client transformation" because the buyer is a firm redesigning its own delivery model around AI. The counterpart is a managing partner or chief innovation officer who needs a peer who speaks audit methodology fluently. Fieldguide's own language — "practitioner-built methodology," "co-developing agents built around Aprio's own methodology" — signals that the commercial team includes former senior associates, managers, and partners from the very firms on the customer list.
Backgrounds cluster in two pipelines. One runs through the Big Four and top-20 firms: audit seniors who automated their own workpapers, managers who built internal tools, partners who championed AI pilots. The other runs through high-growth B2B SaaS: engineers who have shipped LLM features in production, infra engineers who have scaled multi-tenant platforms, and security leads who have navigated SOC 2 and ISO 42001. The overlap is small but decisive. Fieldguide's co-development model — "technology being built with us, to the standards our profession requires" — means every team needs at least one person who has lived the workflow they're automating.
The company's certifications (AIUC-1, ISO 42001, SOC 2) and investor roster (Goldman Sachs Alternatives, Bessemer, 8VC, Thomson Reuters) set a compliance floor that shapes hiring in security and infrastructure. But the differentiator is the product strategy: Field Financials puts coordinated agents on financial statement prep; MCP connects live engagement data to the models firms already use. Both require engineers who can reason about audit standards as first-class constraints, not afterthoughts.
That constraint, professional standards as product requirements, is why the hiring bar resists simple categorization. A Staff AI Engineer who has never read an engagement letter will struggle. A former audit manager who cannot evaluate a retrieval-augmented generation pipeline will stall. The people who stay are the ones who treat the other side's complexity as their problem to solve.
Compensation: What the Numbers Show
Fieldguide pays at the upper end of the early-stage AI startup market. Across Fieldguide's 35 salaried roles posted to the Zero G Talent board, the aggregate band runs $116,000–$260,000 with a median of $210,000, well above the typical Series A/B software-engineer midpoint and signaling that Fieldguide prices talent against the same Bay Area benchmarks as larger AI labs, despite a 65-person headcount.
The individual role bands make the strategy concrete. Engineering roles, Zero G Talent's data shows, span the widest range, reflecting both level breadth and the premium attached to AI-specific expertise:
| Role | Location | Salary Band (USD/year) |
|---|---|---|
| Staff AI Engineer | San Francisco, CA / Remote (US) | $240,000–$310,000 |
| Software Engineer, AgentOps | San Francisco, CA / Remote (US) | $160,000–$310,000 |
| Staff Infrastructure Engineer | San Francisco, CA or Remote (USA) / Remote (US) | $210,000–$295,000 |
| Lead Security Engineer | San Francisco, CA or Remote (USA) / Remote (US) | $210,000–$260,000 |
| Software Engineer (All Levels) | San Francisco, CA or Remote (USA) / Remote (US) | $150,000–$260,000 |
| Strategic Account Partner / Client Transformation | Remote (USA) / Remote (US) | $180,000–$250,000 |
The Staff AI Engineer floor of $240,000 exceeds the Staff Infrastructure Engineer floor by $30,000, a measurable AI premium. The AgentOps role, a newer specialization blending ML ops and product engineering, carries the same $310,000 ceiling as the Staff AI Engineer, signaling Fieldguide values that hybrid skill set at parity with pure research talent. Security leadership tops out at $260,000, below the infrastructure and AI ceilings.
The "Software Engineer (All Levels)" band, $150,000–$260,000, is the widest on the board at $110,000. That spread covers new-grad through senior ICs without separate postings, a practical choice for a lean recruiting team but one that makes the top of band a stronger signal than the bottom. Candidates should assume the upper half requires production LLM experience or equivalent systems depth.
There, that role at $180,000–$250,000 reflects a technical-sales hybrid: the title pairs "strategic account" quota ownership with "client transformation" implementation work. The $250,000 ceiling matches the senior IC engineering ceiling, confirming Fieldguide treats high-leverage customer-facing roles as compensation peers to senior builders.
All listed roles are San Francisco–based or US-remote. No international bands appear in the current board data. The remote designation is consistent across every posting; Fieldguide does not run a split pay scale for geography within the US. That simplicity reduces negotiation friction but also means a candidate in a lower-cost metro is competing against Bay Area cost-of-living benchmarks.
Equity details are not published on the board. The salary bands above are base-only figures; total compensation at the 75th percentile likely adds variable and equity for senior roles. Candidates should ask recruiters for the most recent 409A valuation and option-grant sizing by level, because those numbers move quarter to quarter and the board data captures only the cash component.
Inside the Interview Loop
No Fieldguide-specific interview framework was documented in the research. The company's public materials describe its product and customer engagements but do not publish a detailed hiring process. Candidates should prepare for technical assessments relevant to their track — AI/modeling, AgentOps/ML infrastructure, cloud infrastructure, security compliance, or audit-domain fluency for go-to-market roles — and expect conversations that probe both technical depth and the ability to translate across the practitioner-AI boundary.
Where the Work Happens: A Remote-First Platform Team
Fieldguide operates as a remote‑first company with a single physical anchor in San Francisco. Every role listed there (six postings captured at the time of writing) lists "San Francisco, CA" as an option alongside "Remote (US)" or "Remote (USA)." That role drops the San Francisco option entirely and is listed as "Remote (USA) / Remote (US)." That pattern tells the story: the company maintains a Bay Area foothold for people who want an office, but it does not require anyone to show up there.
The San Francisco address appears on every engineering posting: Staff AI Engineer, Software Engineer (AgentOps), Staff Infrastructure Engineer, Lead Security Engineer, and the general Software Engineer (All Levels) requisition. Those five engineering roles span a board‑reported salary band of $150,000–$310,000. The San Francisco anchor therefore serves the highest‑compensated technical cohort, but it is not a gatekeeper for hiring.
The San Francisco site enables optional in‑person collaboration for the product and engineering teams that build Fieldguide's AI‑native platform. The company's public product pages describe an "AI‑native platform for audit and advisory: planning, testing, review, financials, and orchestration" and a resource library covering "agentic AI architecture and strategy, PBC list building, AI quality assurance." That platform, accessible at app.fieldguide.io and sync.fieldguide.io, is a cloud‑native, browser‑accessible application. The San Francisco office therefore functions as a collaboration hub for the team that ships that cloud product, not as a data center or a hardware lab.
For the majority of the team that works remotely, the capability stack is entirely cloud‑delivered. The platform itself is the primary workspace: audit and advisory teams log in via app.fieldguide.io, authenticate via sync.fieldguide.io, and execute planning, testing, review, and financial workflows entirely in the browser. Fieldguide's own resource library publishes guides on "agentic AI architecture and strategy" and "AI quality assurance," indicating that the internal team uses the same agentic workflows they ship to customers. Remote engineers, product managers, and go‑to‑market staff therefore work inside the very platform they build, planning sprints, reviewing AI‑generated workpapers, and orchestrating releases through the same orchestration layer that customers use.
The remote‑first model also shapes the go‑to‑market footprint. That role is listed as fully remote (USA), with a band of $180,000–$250,000. That role carries quota and works directly with audit and advisory firms that adopt Fieldguide's platform. Because the product is delivered entirely through the browser, the partner can onboard, train, and expand accounts from anywhere in the United States without needing a regional office. The board data shows no postings tied to New York, Chicago, Austin, or other traditional tech hubs; just San Francisco and "Remote (US)."
That geographic concentration has practical implications. Time‑zone alignment is effectively Pacific‑plus‑three‑hours; the company does not currently list roles in European or Asian time zones. Candidates outside the continental U.S. should assume they fall outside the hiring footprint unless a future posting explicitly adds "Remote (Global)" or a specific international hub. The San Francisco office, meanwhile, remains optional; it is useful for whiteboarding a new agentic workflow or onboarding a new hire who wants face time with the founding team, but not a requirement for promotion or project leadership.
Fieldguide's physical footprint is a single San Francisco office that serves as an optional collaboration layer for a cloud‑native platform team. The real workspace is the platform itself (those URLs), which both customers and employees inhabit. The remote‑first policy is not a perk; it is baked into the product architecture.
The Profile That Wins
The board's live postings reveal a hiring pattern that points toward the traits Fieldguide rewards. Every engineering role listed — the roles mentioned above, and the broad Software Engineer (All Levels) bucket — carries a "Staff" or "Lead" designation or explicitly spans all levels, signaling that the company indexes heavily on senior technical judgment. The salary bands reinforce this: Staff AI Engineer at $240k–$310k, Staff Infrastructure Engineer at $210k–$295k, Lead Security Engineer at $210k–$260k, and even the generalist Software Engineer role tops out at $260k. These are not junior-onboarding ranges; they are compensation for people who have already shipped complex systems and can operate with minimal guardrails.
The AgentOps title is itself a tell. It implies a team building and operating autonomous agents, likely the core of Fieldguide's audit-automation product, which means the engineers who thrive there are comfortable with non-deterministic workflows, evaluation pipelines, and the particular chaos of LLM-backed software. The Infrastructure and Security roles at Staff/Lead level suggest a platform that must meet SOC 2 / ISO expectations out of the gate; people who have taken a product through a first audit cycle, or who have built compliant cloud foundations from scratch, will ramp faster than those who haven't.
There, the single listed role, Strategic Account Partner / Client Transformation at $180k–$250k, carries a hybrid title that blends sales motion with implementation ownership. That structure typically appears when the product requires deep domain configuration (here, audit methodology) and the customer success motion is technical enough that a pure CSM can't carry it.
Every role is tagged "Remote (US)" or "San Francisco, CA / Remote (US)." The remote-first default means the traits that predict success include asynchronous communication discipline, the ability to drive alignment without a whiteboard room, and a timezone-aware work rhythm. The board data shows 35 salaried roles across the company with a median band of $210k. LinkedIn reports 201-500 employees, placing Fieldguide in a growth stage where process is codifying but not yet rigid. People who need a runbook for every decision will stall; people who write the runbook as they go will accelerate.
No public employee testimonials, Glassdoor themes, or founder interviews were surfaced in the research to confirm cultural values directly. What the board data does show, consistently, is a preference for demonstrated ownership over credential collection: the levels are high, the domains are narrow (AI agents, audit transformation, secure infrastructure), and the compensation reflects market rates for specialists who can operate independently. If your last three years look like shipping production LLM features, hardening a cloud environment for compliance, or leading a technical implementation for a Top 100 firm, the signal matches. If not, the bar is visible in the bands.
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