Staff Engineer, Agents

MoonPay

5d•Hybrid

About The Position

MoonPay is seeking an exceptional Staff Software Engineer to help own and scale PayBox, one of its newest products. PayBox enables direct transactions through AI, connecting agents with payments, wallets, and applications without requiring users to share their credentials. The role involves working closely with the Chief Engineer and a small, focused team, taking on responsibilities similar to a founding engineer. The engineer will identify key problems, reason through complex challenges, make decisions, and manage product areas from conception to production. This includes designing and building new capabilities, improving onboarding flows, and addressing both ambitious technical challenges and the detailed work required for product excellence. The company is looking for an exceptional generalist engineer who can learn quickly, think independently, build end-to-end solutions, and is deeply committed to the quality of their work. Previous experience in crypto or specific technologies is not required, but a strong aptitude for technical reasoning, high agency, end-to-end ownership, thoroughness, systems thinking, product judgment, comfort with ambiguity, and independent thinking in an AI-native environment are essential.

Requirements

Exceptional technical reasoning. You have strong engineering fundamentals and can break down unfamiliar, ambiguous problems and reason towards good solutions.
High agency. You don’t wait for perfectly defined requirements or someone else to identify what needs doing. You find important problems and take responsibility for solving them.
End-to-end ownership. You’ve built and shipped meaningful products, projects or systems from beginning to end rather than operating within a narrowly defined area.
Thoroughness. You care deeply about the quality of your work and sweat details others might overlook. Getting something working is the beginning, not the end.
Strong systems thinking. You can design systems, understand technical trade-offs and make sensible architectural decisions while moving quickly.
Product judgement. You understand that great engineering includes the experience around the technology, not just the underlying implementation.
Comfort with ambiguity. You’re at your best in environments where there are more problems than people and priorities can change quickly.
Independent thinking in an AI-native environment. You use AI aggressively as a tool, but you don’t outsource your reasoning to it. You understand the output, challenge it and remain accountable for what you ship.
Deep motivation. You want ownership and responsibility and care about the outcome of the product, not simply completing the work assigned to you.

Nice To Haves

Experience as a founding engineer or early engineer at a high-growth startup.
Experience founding and building your own company or product.
Experience taking a product from an idea through launch and subsequent iteration.
Experience operating in small, highly autonomous engineering teams.
Experience building AI-native products, agents or developer tooling.
Experience with payments, fintech, crypto or DeFi.
Previous experience with MCP or other emerging agent protocols.

Responsibilities

Own significant areas of PayBox end-to-end, from identifying the problem and defining the approach through to building, shipping and iterating in production.
Help take a recently launched product through its next phase of 0->1 development and growth.
Build new payment and peer-to-peer transfer experiences designed for AI interfaces.
Build integrations across AI platforms, applications and the wider PayBox ecosystem.
Help develop the infrastructure and product experiences required to bring new applications and integrations onto PayBox.
Work closely with Product to turn ambitious ideas into simple, usable experiences.
Sweat the details of the PayBox experience — particularly onboarding and UX — and fix the friction that prevents users from successfully using the product.
Reason from first principles about difficult technical and product problems, making pragmatic decisions without waiting for perfect information.
Move across different parts of the product and technical stack depending on where the highest-impact problem is.
Use AI extensively to increase your speed and output while maintaining your own technical reasoning, judgement and attention to detail.