About WilliamFrank
WilliamFrank builds one integrated set of agentic rails a wealth team works in.
A small product team, and the work is real from week one. There is no training program.
It helps to picture the firm as a spectrum. Advisors and planners sit with clients. Engineers build the technology. This role sits between the two and tilts toward the engineering end: you design the agents and workflows advisors work in, and then you own whether they actually work.
You will not be advising clients or managing money. This role reports to product leadership and works directly with the founder.
Every role here is AI-native. That is not a preference. If your instinct when handed a repetitive task is to do it carefully rather than to ask what could run without you, this will be a frustrating place to work.
What the job is
You own the operational surface of the product — account opening, transfers, data, documents, the follow-ups that decide whether a household feels looked after. Not by running that work yourself. By designing how an agent runs it, building the workflow, and owning whether the output is right.
If you have done client service or operations at an RIA, a custodian or a broker-dealer and found yourself building spreadsheets and automations to escape the repetitive half of it, this is that instinct as an actual job.
What we are looking for
You do not need a computer science degree and you do not need to have shipped production code. You do need to have built things — agent workflows, automations, scripts, tools — and to be comfortable in an API doc, a spreadsheet and a prompt. SQL and Python are useful. So is exposure to wealth or financial-services operations. Neither is required, and we would rather have someone who has built a lot than someone who has studied a lot.
Systematic enough to hold forty open threads without dropping one, and restless enough to be annoyed that they are holding forty.
Where this goes
Into ownership of the operations surface of the product, or deeper into agent and systems design as the team grows.
Compensation and location
$60,000 – $90,000 depending on experience, plus equity. We are early enough that equity is a real part of the offer.
Full-time and in person. The office is in Lake Oswego and we are hiring across the Portland metro.
How to apply
Skip the cover letter. Send one thing you built with AI that nobody asked you to build — a tool, a workflow, a script, a system for your own life. Tell us in a few sentences what it does, what it replaced, and what you would fix about it.