Lead Product Manager - Agentic AI

About the Role

We'renot looking for a traditional PM who writes Jira tickets and hands them off, and wedon'tneed a backend engineer who wants to stay hidden behind the API.We'restanding up a small, highly autonomous pod to build a net-new agentic AI product inside our Tax & Accounting division, and we need someone who lives at the intersection of product strategy, tax domain logic, and AI capability.

You'llbe the center of gravity for AI execution in the pod: embedded with domain experts to surface complex tax logic, and using agentic tooling to prototype workflows that engineering will harden into production.

One thing to be explicit about up front: WK T&A already ships mature tax calculation engines that encode a lot of the deterministic logic in this domain. *Your job is to orchestrate agentsaroundthat engine — not to reimplement it inside aprompt.*Candidates who understand why that distinction matters will do well here.

What You'll Actually Do

• Prototypes and evals are the spec.Instead of long PRDs,you'llship high-fidelity agent prototypes and the eval suites that define "done." Prototypes prove value; evals define correctness. Engineering scales what survives both.

• Own the eval framework.Tax software has to be right.You'lldesign prompts, define tool-use constraints, and build the eval harness (with engineering) that measures accuracy, catches hallucinations, and traps logic failures before they reach aclientreturn.

• Bridge the translation gap.Decompose ambiguous tax jobs-to-be-done into structured agent architectures — multi-agent orchestration, state management, human-in-the-loop decision points — that engineering can build against.

• Own theuniteconomics.Balance model accuracy against latency and inference cost. A 20-step multi-agent loop might solve the problem; you decide whether it can ship at a commerciallyviablegross margin, and design cheaper paths when itcan't.

• Design for graceful degradation.Enterprise users have zero tolerance for infinite spinners or confidently wrong answers.You'lldesign explicit fallbacks: when the agent hits ambiguity, the system steps down to deterministic rules from the calc engine, or routes to a human — visibly and predictably.

• Partner with tax SMEs.You are not expected to be a tax expert.You'llwork side-by-side with our internal domain experts, translating their judgment into system prompts, tool contracts, andevalcriteria. Building trust with SMEs is part of the job; they are collaborators, not a resource to be mined.

Ultimately, youown the journey from opportunity identification through validated prototype, evaluation performance, and production launch. Success is measured by customer adoption, task completion accuracy, and business impact, not document output.

Who's Around You

This is a small pod, but itisn'ta solo role.You'llpartner with:

• Engineering

• UXDesign partner

• Tax domain SMEs

We call this out because agentic AI in a regulated domainisn'ta one-person job.If any of those capabilities aremissing,identifyingthegapand helping build the right team around the product is part of the role.

The Profile We're Looking For

• AI power user.Youdon'tneed to write production Python from scratch, but you are a daily practitioner of agentic tooling.You'veorchestrated real work using agentic development environments such as Claude Code, Cursor, Copilot, or similar tools.

• Transcript debugger.When an agent gets stuck or hallucinates, your first move is to open the raw transcript. You can tell whether the failure was a bad prompt, a missing tool, an eval gap, or a genuine model limitation — and you know which of those to fix first.

• Systems thinker.You understand context windows, RAG, model routing, tool design, and — crucially — when a deterministic rule or a call into an existing engine is the right answer instead of an LLM call.

• Comfortable in the gray.Traditional software is deterministic; agentsaren't. You havea track recordof shipping UX that handles AI uncertainty honestly — fallbacks, confidence signals, human-in-the-loop validation — without hiding the seams from users who need to trust the output.

• Commercial pragmatism.You have a bias for time-to-market. You know when to compose third-party APIs and when to invest in proprietary orchestration.

• Regulated enterprise SaaS experience.You'veshipped commercial software into environments where compliance, data privacy, auditability, and uptime are non-negotiable. Bonus ifthat'sbeen in tax, accounting, legal, healthcare, or financial services.

Ifyou'rea high-agency builder who wants to shape the future of commercial tax software from the ground up, we want to talk.