新石器 AIBP 团队招聘：FDE 前向部署工程师（应届 / AI 原生） / New Grad Forward Deployed Engineer

新石器 AIBP 团队招聘：FDE 前向部署工程师（应届 / AI 原生） New Grad Forward Deployed Engineer, AIBP Team 地点 / Location: 北京 / Beijing, China 工作方式 / Work Mode: 现场办公 / Onsite 关于团队 AIBP 团队负责把 AI 真正落到业务场景中。你会和资深 FDE 或业务团队一起，把最新模型、Agent 工具和工程能力转化成真实可用的业务应用。 About the Team The AIBP team brings AI into real business workflows. You will work with senior FDEs and business teams to turn frontier models, agent tools, and engineering capabilities into usable business applications. 一句话定位 对最新模型和 Agent 工具如数家珍、自己折腾过一堆项目、学习和动手速度快到吓人的 AI 原生工程师。 Role in One Sentence An AI-native engineer who knows the latest models and agent tools, has built many things independently, and learns and ships extremely fast. 你会做什么 - 跟着资深 FDE 或独立认领，扎进业务场景做 AI 应用快速原型与端到端交付。 - 持续跟踪前沿模型、Agent 框架和工具，并第一时间在真实业务上验证。 - 在试点 BU 中亲手证明一个人能带一队 Agent。 - 用最新工具快速试错，把可行方案推到真实使用。 What You Will Do - Build rapid prototypes and deliver AI applications end to end in real business scenarios. - Track frontier models, agent frameworks, and AI tools, then validate them in production-like business contexts. - Help demonstrate how one person can orchestrate a team of agents in a business unit. - Test quickly, learn quickly, and turn promising ideas into real usage. 我们希望你具备 - 顶尖院校计算机 / AI 相关专业本科或硕士，应届或毕业 1–2 年。 - AI 原生，有开源项目、Hackathon、个人产品、Side Project、技术博客等作品。 - 工程基本功扎实，熟悉 LLM / Agent 生态。 - 能独立把一个想法做成跑得起来的东西。 - 主动、学习快、敢钻进陌生业务、出活快。 What We Are Looking For - Top university CS or AI background, new graduate or 1–2 years out of school. - AI-native builder with visible work such as open-source projects, hackathons, personal products, side projects, or technical writing. - Strong engineering fundamentals and familiarity with the LLM and agent ecosystem. - Ability to turn ideas into working products independently. - High initiative, fast learning speed, and willingness to enter unfamiliar business contexts. 加分项 - 有真实用户使用过的个人作品或开源项目。 - 拿过竞赛或 Hackathon 名次，或在 AI 社区有产出。 - 有创业或独立开发经历。 Nice to Have - Personal or open-source projects used by real users. - Competition or hackathon awards, or visible contributions in AI communities. - Startup or indie-hacking experience.