Member of Technical Staff - App Engineer

ai& is a new global AI technology company dedicated to meeting the world's growing demand for AI. Our vision is twofold: to serve as a premier AI lab specializing in localization, and to act as a global infrastructure and compute provider. We are building a unified, optimized global platform that integrates next-generation data centers and infrastructure, heterogeneous compute serving, and advanced model services. We believe that the most effective way to build and scale AI is to own the stack from top to bottom.

At ai&, we empower small teams with the autonomy needed to tackle significant challenges. Our approach is to deconstruct large problems into manageable components and solve complex issues collaboratively. We seek highly motivated, mission-driven individuals who demonstrate strong personal agency. We value curiosity as the foundation of talent, and we are looking for people eager to develop alongside our evolving technology and expanding business.

We are actively hiring worldwide, with presence in Tokyo, SF, Austin, and Toronto. We are more than happy to meet exceptional talent where they are.

You will take products from concept to production.

This is a hands-on building role. Product direction is shaped with the founders; your job is to turn that direction into software people in Japan want to use.

You will work across product design, frontend, backend integration, and deployment. Once something ships, you will stay close to it—learning from users, improving the experience, and shipping continuously.

Our development workflow is AI-native. AI writes a meaningful portion of the code, and we expect you to use it aggressively to move faster. What we cannot hand to a model is judgment: what to build, how it should feel, whether the architecture makes sense, and whether the final result is actually good.

That requires technical depth. You do not need to be the strongest low-level engineer in the room, but you do need to understand the stack and current AI models well enough to direct the work, maintain sound architecture, and catch subtle problems before users do.

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  Build and ship web and mobile products from initial concept and design through backend integration and deployment.

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  Own the product experience end to end. Typography, spacing, motion, empty states, responsiveness, and the moment between tapping and seeing a result are all part of the job. Design is not handed off here.

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  Use AI aggressively to prototype and build faster while remaining the final judge of quality, logic, and engineering decisions.

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  Work directly with our inference and post-training teams to shape APIs and model capabilities around real product needs.

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  Put working software in front of the team every week and continuously improve what has already shipped.

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  Talk directly to users and turn what you learn into better products. Creative users in Japan have specific expectations and taste, and understanding them is part of the role.

• You have shipped at least one product end to end, put it in front of real users, and can show us what you built.

• You move quickly and find a way through roadblocks. You prefer getting working software into users' hands over spending too long perfecting something in isolation.

• You have strong visual taste and care about details. Design is part of how you build, not something added at the end.

• You are technically grounded. You understand modern software stacks—and the capabilities and limitations of current AI models—well enough to review AI-generated work and maintain a high engineering bar.

• You are comfortable working across product, design, and engineering rather than staying within a narrow function.

• You communicate clearly and work well in a small, fast-moving team.

• You are fluent in English. Japanese is a strong plus.

We have a particular interest in former founders and people who have built something of their own.

If you have started something, shipped it, put it in front of users, and lived with the consequences of your own product and technical decisions, we want to talk—whether or not it ultimately worked.