We design and sell products for the global market. Our first product is an AI smart ring designed for fast voice capture and agent interaction.
Alongside the hardware, we are building a software platform that allows users to interact with agents, and an SDK that enables OEMs and developers to connect third-party devices to our apps.
We are also inspired by projects like OpenClaw in our belief that users should have far more flexibility and control over how agents operate. Over time, we aim to build a configurable environment where consumers can choose and use any tool, any harness, any model, and any sandbox through a unified product experience.
Responsibilities
This role focuses on implementing agent execution logic, tool integrations, and core system infrastructure. It is a hands-on engineering role centered on writing production code, shipping quickly, and building real systems.
• Implement execution logic and core functionality for action-oriented AI agents
• Write code that integrates with user tools and systems (APIs, apps, and services)
• Build systems for task execution, state updates, and result handling
• Develop and maintain scalable AI and shared services such as agent harnesses, tool use frameworks, sandboxes, workflows, and chat systems
• Help build a configurable agent environment that can support different tools, harnesses, models, and sandboxes in a flexible way
• Integrate LLMs, computer vision models, and recommender systems into mobile and web clients
• Build and maintain reliable backend infrastructure for payments, rewards, order routing, and analytics
• Write maintainable, testable production code and fix real-world bugs and edge cases
• Ship quickly and iterate continuously in a small, high-velocity team
Requirements
• 2–3+ years of software engineering experience
• Strong programming fundamentals and engineering discipline
• Experience with at least one backend or systems-level language (such as TypeScript / Node.js)
• Familiarity with modern web development stacks
• Experience coding with AI tools such as Cursor or Claude Code
• Up-to-date knowledge of the modern AI development ecosystem
• Interest in building real, production software systems
• Willingness to work on core execution logic, infrastructure, and backend systems
Nice to Have
• Experience building automation bots or AI agents
• Experience with the Cloudflare developer stack (D1, R2, Durable Objects, Agent SDK, etc.)
• Familiarity with OpenCode, Letta, OpenClaw, or other agent execution frameworks
• Cloud or DevOps experience (Supabase, Planetscale, AWS/GCP, containers, infrastructure-as-code)
How We Work
• Tiny team with high autonomy
• Daily release cadence and fast iteration
• Data-driven product development
• We believe consumers should eventually be able to use any tool, any harness, any model, and any sandbox through one configurable system
• “Build it, run it” ownership mindset
软件工程师 / Software Engineer
我们打造用于与 AI 智能体交互和下达指令的消费级硬件设备。
我们面向全球市场设计和销售产品。第一款产品是一枚用于快速语音记录和智能体交互的 AI 智能戒指。
在硬件之外,我们也在构建一套软件平台,使用户可以通过应用程序与智能体交互。同时我们也会提供 SDK,使 OEM 厂商和开发者能够将第三方设备接入我们的应用。
我们的产品理念也受到 OpenClaw 等项目的启发。我们相信用户应该拥有更大的自由度来配置智能体系统。长期来看,我们希望构建一个可配置的环境,使消费者可以自由选择和使用任意工具、任意智能体执行框架、任意模型以及任意 sandbox,并通过统一的产品体验来进行管理。
工作职责
该岗位主要负责实现智能体执行逻辑、工具集成以及核心系统基础设施,是一个以编写生产级代码、快速迭代和构建真实系统为核心的软件工程岗位。
• 实现行动型 AI 智能体的执行逻辑与核心功能
• 编写与用户工具和系统交互的代码(API、应用、服务等)
• 构建任务执行、状态更新与结果反馈等核心系统
• 开发和维护可扩展的 AI 与共享服务,例如智能体执行框架、工具调用系统、sandbox、workflow 和聊天系统
• 参与构建可配置的智能体运行环境,使系统能够支持不同工具、执行框架、模型和 sandbox 的灵活组合
• 将 LLM、计算机视觉模型和推荐系统集成到移动端和 Web 客户端
• 构建和维护稳定的后端基础设施,包括支付、奖励系统、订单路由和数据分析
• 编写可维护、可测试的生产级代码,并修复真实使用场景中的 bug 与边界问题
• 在小团队环境中快速开发和持续迭代产品
任职要求
• 2–3 年以上软件工程经验
• 扎实的编程基础和工程能力
• 熟悉至少一门后端或系统级编程语言(例如 TypeScript / Node.js)
• 熟悉现代 Web 技术栈
• 有使用 AI 编程工具的经验(例如 Cursor、Claude Code 等)
• 持续关注并了解最新的 AI 开发生态
• 对构建真实可用的软件系统有兴趣
• 愿意长期投入在执行逻辑、系统基础设施和后端工程开发上
加分项
• 有自动化机器人或 AI Agent 开发经验
• 有 Cloudflare 开发栈经验(D1、R2、Durable Objects、Agent SDK 等)
• 熟悉 OpenCode、Letta、OpenClaw 或其他智能体执行框架
• 具备云基础设施或 DevOps 经验(Supabase、Planetscale、AWS / GCP、容器化、基础设施即代码等)
工作方式
• 小团队,高度自主
• 高频发布节奏,持续快速迭代
• 数据驱动的产品开发方式
• 我们相信未来消费者可以通过一个系统使用任意工具、任意执行框架、任意模型和任意 sandbox
• “Build it, run it”的工程文化,对系统全生命周期负责