Senior Product Manager

Description

The company started by issuing corporate cards and bank accounts to creators, the people with large YouTube, Instagram, TikTok and Twitch audiences who run real businesses but were overlooked by most financial providers.

The same products now suit a wider group, including agencies, studios and fast-growing companies that operate in similar ways, alongside creators.

The company has raised $70 million from Signal Fire, Union Square Ventures, Y Combinator, CRV and Coatue. Backers also include CEOs from YouTube, Twitter and Wealthfront, and Twitch co-founder Kevin Lin.

The team has people from Goldman Sachs, McKinsey, earlier startups and the creator world. The company is headquartered in Los Angeles.

The company decides who gets a card and what credit limit they receive, holds customer deposits and moves customer money. Each of those decisions goes through a product, an internal tool or a person on the operations team. This role owns the product thinking behind them.

This role leads product for the operational core: how businesses apply, how decisions get made, and the internal tools that operations, compliance and support use to review, approve and serve customers. The aim is for an engineer to pick up work where the problem is framed, edge cases are mapped, the design has been reviewed, and operations and compliance have weighed in.

The scope has two sides. Internally, tooling and automation so a small operations team can handle more volume with better decisions. Externally, the application and the card products people sign up for, including what happens when an applicant does not qualify for the product they wanted.

This is a hands-on product role. You write the PRD, build clickable prototypes before design review, pull your own data, watch session recordings, and ship small changes with AI tools when waiting for an engineer would be slower. You work directly with the executive leadership team and a small, fast engineering team that expects the thinking to be finished before they start.

Responsibilities

• Own the product thinking for your area from start to finish: the problem statement, PRD, edge cases, design review and launch, so engineering receives work that is ready to build.
• Run discovery with the people doing the work. Sit with operations and compliance as they review applications, read support threads and watch session recordings, then rank recurring friction into the few fixes that remove most of the pain.
• Build clickable prototypes and working slices with AI tools such as Claude Code, Cursor, Lovable, v0 or whatever you prefer, so reviews start from something concrete rather than a written description.
• Write your own SQL, define the success metric before a feature ships, and report the result afterward.
• Decide where AI should recommend and where it should decide in operational workflows. Define the evals, the override path for operators, and what gets logged.
• Set priorities from first principles. Requests come from customers, partners, operations and leadership, but the roadmap follows throughput, risk and customer trust. Say no clearly and in writing.
• Keep the engineering loop tight by scoping, sequencing, cutting and unblocking, so a two-week project takes two weeks.
• Apply the same quality bar to internal tools as to customer-facing ones, since the people using them all day depend on them and that is where throughput comes from.
• Document decisions, tradeoffs and lessons in a form that engineers, operations and the executive team can act on without a meeting.

Requirements

• 4+ years in product management, or the equivalent as a founder or an engineer who owned product decisions at a company with no one else to hand the hard parts to.
• You build. You have shipped prototypes or small features with AI coding tools, can read code and a database schema, and write SQL to answer your own questions. You will be asked to show something you made.
• Fintech or finance experience in lending, underwriting, payments, banking or another regulated product where ship-and-learn has limits, and you know where those limits are.
• You have built for internal users doing high-stakes work in operations, compliance or support, and treated them as customers.
• You define the problem and success metric before writing the spec, and can point to a time your discovery changed what was built.
• You make calls under ambiguity, decide what is now, next and never, and change course when the evidence shifts.
• You write clearly. PRDs, decision memos and launch notes are readable the first time.
• You have design taste. You can sketch a flow, critique a mock and tell finished work from good work.
• You are based in Los Angeles or willing to relocate.
• You have shipped or evaluated an AI feature in production, including prompts, evals, override paths and what happened when it was wrong.
• You have worked on KYC or KYB, underwriting, credit decisioning or risk operations.
• You were a founder or the first PM at a company.
• You use session replay tools such as LogRocket, Linear and Figma daily.

Conditions

Based in Los Angeles, or willing to relocate.

6+ years of experience.

Open only to US citizens or visa holders.

Benefits

• Growth: the company is well capitalized but keeps the team lean, so this is a rare seat. You will learn a lot, build foundational products and grow as the company scales.
• Impact: you set up discovery, specs and launches from scratch, and the first thing you ship will be used by your teammates the next morning.
• Team: the group includes previous founders, operators from banking and payments, and engineers from top companies, all hands-on and small enough that everyone knows each other's work.
• Ownership: the company wants people who improve the product rather than maintain it, own their work and get things done, without waiting for permission.