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Open nowPosted 47 days ago

AI原生运行时开发工程师

li/referral788 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen nowAI原生运行时开发工程师li/referral · Beijing, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on li/referral's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. li/referral postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 47 days ago

li/referral median: 1 days open

The posting

负责构建面向 AI Agent、智能工作流和大模型应用的下一代运行时基础设施，聚焦 Serverless 执行架构 与 Sandbox 安全执行环境，打造高弹性、低延迟、强隔离、可观测的 AI 原生执行平台，为智能体任务调度、工具调用、代码执行、数据处理等场景提供稳定可靠的底层能力。

1. 基本要求 1.1. 计算机相关专业本科及以上学历，具备扎实的计算机基础，熟悉操作系统、计算机网络、并发编程、数据结构与算法。 1.2. 具备 3 年及以上后端或基础架构开发经验，有分布式系统、云原生平台、运行时系统相关经验者优先。 熟练掌握至少一门系统或服务端开发语言，如 Go / Rust / Java / C++ / Python，其中具备 Go 或 Rust 经验优先。 1.3. 熟悉 Linux 系统原理，理解进程、线程、内存管理、文件系统、Namespace、cgroups、seccomp 等机制。 1.4. 具备良好的系统设计能力，能够独立负责复杂模块的架构设计、开发实现和稳定性治理。 2. Serverless 方向要求 2.1. 理解 Serverless / FaaS / 容器调度基本原理，熟悉函数执行生命周期、弹性伸缩、冷启动、实例复用、事件驱动架构等核心机制。 2.2. 有以下一个或多个方向的实践经验：Knative / OpenFaaS / Kubeless / AWS Lambda / Cloud Run 等 Serverless 平台 2.3. Kubernetes 调度、控制器开发、Operator 开发 2.4. 异步任务编排、事件驱动系统、队列系统、任务执行引擎 2.5. 具备运行时性能优化经验，能够围绕冷启动时延、资源利用率、吞吐能力、任务调度效率进行系统级优化。 3. Sandbox 方向要求 3.1. 理解多租户隔离与安全执行的基本原理，具备沙箱执行环境设计或开发经验。 3.2. 熟悉一种或多种隔离/沙箱技术：Linux Namespace / cgroups / seccomp / AppArmor / SELinux gVisor / Firecracker / Kata Containers / Wasm Runtime Docker / containerd / CRI-O 等容器运行时 3.3. 理解恶意代码防护、资源逃逸防护、网络隔离、文件系统隔离、权限最小化等安全设计原则。 4. AI 原生相关加分项 4.1. 了解 LLM / Agent / Workflow 的基本执行模式，理解 Tool Calling、Code Interpreter、Memory、任务编排等场景对 runtime 的要求。 4.2. 有 AI Agent 平台、模型服务平台、工具执行框架、代码解释器、自动化工作流引擎等相关项目经验。 4.3. 熟悉 AI 应用场景下的流式执行、长任务管理、状态恢复、结果缓存、可观测和成本治理。 5. 通用加分项 5.1. 熟悉 Kubernetes、Istio、Prometheus、Grafana、OpenTelemetry 等云原生和可观测技术栈。 5.2. 熟悉 Redis、Kafka、NATS、RabbitMQ、PostgreSQL 等基础组件。 5.3. 有高并发、高可用、分布式调度、资源管理平台经验者优先。 5.4. 具备良好的跨团队协作能力、问题分析与排障能力，对新技术有持续学习热情。

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