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Agent的下一代智能板端OS。\nCUDAGen 学术化：方法体系沉淀为论文对外发表。\n岗位职责\n参与 AI 平台类产品（CUDAGen / 数据 Agent / Agentic 平台 / 板端 AIOS）从 0-1 的设计与端到端研发。\n负责 LLM Agent 系统建设：Prompt 工程、Agent 编排、工具链集成、多轮自迭代优化与评测体系。\n设计并实现 Agentic 平台 核心能力：编排引擎、工具调用框架、记忆与上下文管理、评测闭环，输出标准化的 Agent 应用开发范式。\n推动 AI 平台与自研芯片软硬件栈深度集成（编译工具链 / 算子库 / 端侧推理运行时），形成差异化壁垒。\n沉淀面向自研芯片场景的领域知识库与策略模板，持续提升 AI 生成质量与稳定性。\n探索板端 AIOS 的 Agent 运行时、异构调度与端云协同方案。\n平台工程：服务架构、API、任务调度、负载均衡、可观测性。\n参与 CUDAGen 论文方法整理与撰写。\n任职要求\n本科及以上，计算机相关专业，3 年以上研发经验。\n扎实 Python 工程能力，熟悉 FastAPI、Docker、Git 工作流。\n有 LLM / Agent 应用落地经验：Prompt 工程、工具调用、Agent 编排、评测闭环。\n具备产品化思维，能独立从需求走到上线，跨团队协作能力强。\n加分项（任一即可）\n有 Agentic 平台 / Agent Framework 设计或贡献经验（LangChain / AutoGen / LangGraph / Dify / 自研 Agent 平台等）。\n熟悉 自研芯片 / 异构算力生态：CUDA、PTX / SASS / NCU、Tensor Core、shared memory 优化，或自研 ISA / 编译工具链 / 算子库。\n端侧 AI / AIOS 经验：Edge AI、端侧推理加速、CPU / GPU / NPU 异构调度、端云协同架构。\n数据栈：SQL 优化、数仓、BI / 可视化。\n有顶会 / 期刊论文经验，或愿意参与学术化产出。\n有 0-1 主导 AI 平台 / DevTool 产品经验。\n加入我们能获得\nAI × 自研芯片全栈视角：从 LLM Agent 应用，到芯片工具链与端侧 AIOS，纵向贯穿。\n横跨 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