GenAI Native Product Engineer

About the position

We're building GenAI-native experiences that feel inevitable. This isn't about AI hype — this is about rewriting how product and engineering collaborate to create developer joy, automate friction, and deliver smart, fast, lovable tools. You'll be one of the first few team members on a new internal “strike team” focused on rapid iteration, internal innovation, and product-grade execution. You will prototype fast, fail beautifully, and ship things users want before they know they want them. Think of it as: building a startup inside a fintech, but with actual backing, access to production APIs, and direct lines to leadership.

Responsibilities

• Build fast. Think Replit-native: zero boilerplate, maximum outcome.
• Pair with Product to prototype new ideas, test UX patterns, or redesign something broken — often in days, not weeks.
• Work closely with LLMs, vector DBs, and modern orchestration frameworks (LangChain, LlamaIndex, OpenAI, Claude, etc.).
• Build user-facing stuff (React, Tailwind, Next.js) and backend flows (Python, FastAPI, etc.) or whatever tool gets the job done.
• Design for love, not just function. We don't do clunky tools. We obsess over magic.
• Think modularly. Build in a way that lets others build on top of your work.
• Iterate in public (internally) demo, test, repeat.
• Collaborate with one of the sharpest GenAI-native minds in space (yes, we mean your manager).

Requirements

• You've shipped products or tools powered by GenAI — not just toy projects, but things people use.
• You've used Replit or similar environments and believe coding should be joyful and frictionless.
• You can work independently but know when to bring others in for magic.
• You think in components, flows, and feedback loops — not just code.
• You've played with LangChain, OpenAI, or even built your own agentic workflows. You know where the hype ends and the craft begins.
• You're not afraid of ambiguity — in fact, you love shaping the problem.
• You've built or hacked on developer tools, internal platforms, or early-stage AI experiments.
• You care about UX. You can argue about button spacing if needed.