Senior Software Engineer, Full Stack (Zero to One Labs)

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.

Zero To One (ZT1) is Affirm’s 0 -> 1 innovation lab, focused on turning bold ideas into validated new businesses. Operating outside the standard Product and Engineering structure, ZT1 is built for speed, autonomy, and decisive execution. We run fast, hypothesis-driven experiments with a clear goal: prototype quickly, generate real signals, and drive explicit “kill or scale” decisions on high-impact opportunities, with AI as a core enabler across the stack.

As an engineer on ZT1, you will work in a small, highly empowered, AI-native team alongside product managers and cross-functional partners, with direct exposure to senior leadership. You will not just build systems, you will help shape experiments, define technical approaches, and influence product direction. Work happens in rapid sprint cycles, where ideas quickly move from concept to AI-powered prototypes and real-world testing.

Engineers on this team are expected to be comfortable leveraging AI-first tools and approaches, including AI-assisted development, agentic workflows, automation, and rapid prototyping. You should have an eye for product and design, and be able to quickly translate ideas into functional, AI-enabled prototypes that can be tested with users or stakeholders.

This role is ideal for engineers who thrive in ambiguity, move quickly, and take ownership end to end in an AI-centric environment. You will balance speed with sound engineering judgment, contributing to both early prototypes and scalable AI-driven solutions when ideas prove viable. If you enjoy building from scratch and seeing your work directly impact company strategy, ZT1 offers a uniquely high-leverage environment.

What You'll Do

· You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguit