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Open nowPosted 1079 days ago

LLM Agent基础架构工程师-TRAE

ByteDance19,198 open roles

Where
Hangzhou, Zhejiang, Chinese Mainland
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Your applicationOpen nowLLM Agent基础架构工程师-TRAEByteDance · Hangzhou, Zhejiang, Chinese Mainland

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 1079 days ago

ByteDance median: 2 days open

The posting

团队介绍：TRAE（The Real AI Engineer），是字节跳动旗下的AI编程产品，一个能理解需求、调动工具、独立完成开发任务的AI开发工程师，为用户提供端到端生成真实软件的服务。TRAE是当前国内受到广泛欢迎的AI编程产品之一，也是业界首个端到端AI软件开发Agent产品，可覆盖简单到复杂全场景。我们正在寻找充满热情、富有创造力的人才。期待你的加入，与我们共同重塑开发范式，定义未来开发的形态。

1、负责TRAE IDE/Coding Agent核心后端系统研发，支撑代码补全、代码理解、代码生成、测试生成、任务执行等AI编程场景，持续提升开发者在IDE内的端到端AI体验； 2、建设大模型接入与调度基础设施，负责多模型接入、模型能力抽象、模型路由、Streaming、Function Calling/Tool Calling、长上下文、降级容灾、限流治理、成本优化等能力，支持不同AI IDE场景下的差异化模型调用策略； 3、建设Coding Agent所需的工程基础设施，包括Agent Runtime、Harness Engineering、Context Engineering、Prompt管理、实验平台、AB测试与Tracing体系，支撑Agent的任务编排、工具调用、上下文构造、执行链路追踪、效果评估和持续优化； 4、面向Agent范式下的特殊流量模式进行系统优化，重点解决代码补全等低延迟高频请求，以及Chat/Agent长任务中的高并发模型调用、流式响应、多轮工具调用、请求取消/重试、模型限流排队、Token成本和商业化计费等问题。

1、本科及以上学历，计算机相关专业，3年以上后端研发、基础架构研发或平台系统研发经验；具备扎实的软件开发基本功，熟练掌握Golang、Java、Python、C++中至少一种编程语言； 2、具备优秀的后端架构设计和工程交付能力，能够独立设计并落地高可用、高并发、可扩展的平台型系统，熟悉缓存、队列、异步任务、限流、熔断、降级、灰度发布、可观测性、成本治理等基础能力； 3、深入理解LLM应用研发技术栈，熟悉主流大模型及API的能力边界和工程化特点，了解模型路由、流式输出、工具调用、Prompt Caching、Rate Limit、上下文窗口、Token计费、结构化输出等机制； 4、具备Agent应用开发或优化经验，理解Agent Loop、任务分解、多轮工具调用、上下文构造、状态管理、失败恢复、结果验证、Tracing、实验评估等核心机制，能够端到端分析和优化Agent应用效果； 5、熟悉AI IDE/Coding Agent相关场景，对代码补全、代码生成、代码检索、测试执行、PR生成、开发者工作流等场景有实践经验或深入理解；能够针对低延迟高频请求和长任务Agent请求设计差异化的系统架构与优化策略。

加分项： 1、有AI IDE、Coding Agent、LLM Gateway、Agent Runtime、Prompt管理平台、LLM Tracing、实验平台、代码补全、商业化计费等系统建设经验； 2、对相关产品或框架有深入使用和工程理解。

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