Founding Product Engineer

Cranston is building the AI back office for CPA firms. This role turns messy tax prep, bookkeeping, client-request, and firm-operations workflows into shipped product inside live accounting firms.

You will own product surfaces from ambiguous problem to shipped workflow. That means understanding how the work happens inside CPA firms, deciding what the product should do, using AI agents as your primary implementation layer, and tightening the result until it is fast, clear, and trustworthy.

About the role

This is a product engineering role for someone who wants to build, not just spec. You will spend time with users, but the job is not to be a consultant or an implementation manager. The job is to turn what we learn from firms into durable product: workflows, interfaces, automations, review loops, data models, and agent behavior that work across customers.

You will use AI agents as your primary implementation layer, but you still need product judgment and enough technical fluency to know when the system is right. You should understand how modern software fits together, be comfortable around GitHub and Postgres, and be able to reason about product behavior from logs, database state, screenshots, and customer feedback.

The best person for this role is high-agency, product-minded, technically fluent, and unusually good at turning ambiguity into a concrete next move. You should care about product quality, move quickly, and be willing to use the product yourself until the rough edges are gone.

About Cranston

Cranston was founded by Sean O’Bannon and Max Minsker to rebuild the accounting firm back office from the ground up. Sean previously built ERP and automation systems at ReMatter and Databricks, seeing how much labor still sits on top of even the best systems of record. Max ran an accounting firm that filed 10,000+ tax returns and saw the same problem from inside the work itself: firms losing their best hours to document chasing, data entry, reconciliations, cleanup, and handoffs.

Our view is that the next generation of accounting firms will not run on bigger offshore teams or more disconnected point solutions. They will run on AI agents that can understand firm context, do the repetitive prep work, and leave the judgment calls to experienced accounting professionals. We are building that back office: the system that helps CPA firms take on more work, serve clients faster, and give accountants their time back.

What you will do

• Own product workflows for tax prep, tax review, bookkeeping, client requests, and practice-management operations.
• Turn messy customer and operator feedback into clear product decisions: what to build, what to simplify, what to automate, and what needs human review.
• Use Cranston's internal agent platform to move from product context to working software quickly.
• Drive AI-agent implementation loops, review the product behavior, inspect the underlying data when needed, and keep improving the workflow until it works in real usage.
• Design and refine interfaces that make complex accounting work feel simple, trustworthy, and reviewable.
• Use the product yourself, notice what is wrong, and push the system until the details are right.
• Work with engineering, accounting, and operations to turn one-off customer pain into reusable product.

What you will do in your first 30 days

• Learn how CPA firms move work from source documents to reviewed tax packages, books, and client follow-ups.
• Shadow existing Cranston workflows and identify places where better product behavior would remove real manual work.
• Pick workflows and turn them into a concrete product plan: inputs, user-facing states, edge cases, success criteria, and verification steps.
• Drive an AI-agent implementation loop from product plan to working feature.
• Test the workflow yourself against real or realistic data, fix the rough edges, and help ship it into a live customer or internal operator workflow.

Who we are looking for

• You are remarkable in some way that is hard to fake. You may have been unusually good at games, music, writing, sales, math, building internet things, or a niche obsession most people do not understand.
• You are product-minded, good at understanding systems, and unusually fast at turning ambiguity into a concrete next move.
• You should be technically fluent enough to work effectively with AI coding agents and judge whether the output actually solves the problem.
• We care much more about raw ability, taste, curiosity, and output than traditional credentials.
• You are comfortable using AI coding agents as your main implementation tool and holding their output to a high bar.
• You are probably a Lovable, Replit, Cursor, Claude Code, or Codex power user. You have built apps, internal tools, automations, websites, or strange little products because you could not help yourself.
• You have a bias toward the simplest thing that could possibly work, especially when everyone else is making the problem sound more complicated than it is.

Interview Process

Our process is lightweight and practical. We want evidence that you can understand a messy workflow, turn it into a concrete product direction, and use agents to ship useful software.

Typical process:

1. Intro conversation about your background and what you have built.
2. Practical product/workflow exercise using a real or realistic back-office workflow.
3. Founder conversation focused on taste, pace, customer empathy, and how you work with AI agents.

We try to move quickly and keep the process tied to the actual work.