主要职责 /Responsibilities

● 平台架构与技术路线/Platform Architecture & Roadmap
在云、混合或本地环境设计并实现安全、可扩展、可靠的 AI 平台；制定技术选型、平台演进路线图与最佳实践。
Design and implement secure, scalable, reliable architectures (cloud/hybrid/on‑prem); define tech choices, a roadmap, and best practices.

● 交付与运营/Delivery & Operations
统筹 AI 服务与平台的开发、部署与运行；规范版本与变更流程，确保稳定与效率。
Oversee development, deployment, and operations; standardize release/change management to ensure stability and speed.

● 指标监控与性能优化/ Observability & Performance Tuning
监控系统指标、分析瓶颈并推进性能调优；制定高可用/可靠/可扩展策略，主动识别并解决平台问题。
Monitor metrics, analyze bottlenecks, drive tuning; craft HA/reliability/scalability strategies and proactively resolve platform issues.

● 安全、合规与灾备/ Security & Compliance
将安全最佳实践融入 DevOps；确保平台的安全、合规与灾备就绪
Integrate security best practices into DevOps; ensure platform security, compliance, and disaster‑recovery readiness (drills, auditability)

● 业务协同与沟通/ Communication & Collaboration
与产品、数据科学、业务团队对齐平台能力与目标；把复杂技术方案清晰传达给非技术干系人并推动落地
Align platform capabilities with product/data/business objectives; communicate complex topics to non‑technical stakeholders and drive execution

任职要求/Qualification

● 学历
计算机、工程、信息技术、人工智能等相关本科或硕士
Bachelor’s or Master’s in Computer Science, Engineering, IT, AI or related fields

● 平台与云
熟悉 AI/ML 平台架构与主流云（AWS / Azure / 阿里云），能在云、混合、本地环境搭建平台。
Deep knowledge of AI/ML platform architecture and major clouds (AWS / Azure / AliCloud); able to build in cloud, hybrid, and on‑prem settings.

● DevOps 与工具链
熟练使用 Jenkins / GitLab / Docker / Kubernetes / Terraform / Ansible 等；有CI/CD、基础设施即代码（IaC）、自动化测试与监控的实操
Hands‑on with Jenkins, GitLab, Docker, Kubernetes, Terraform, Ansible; practical CI/CD, IaC, automated testing, and monitoring

● 编程与脚本
能用 Python / Java / Scala / Bash 完成开发与自动化
Strong coding in Python / Java / Scala / Bash

● 性能与扩展
有性能/可扩展性调优经验，理解算法与计算复杂度，能定位并解决瓶颈
Experience in performance & scalability tuning, algorithms, and computational complexity; able to diagnose bottlenecks

● 安全与合规
了解企业环境中的安全、合规与灾备（含演练与恢复目标）
Familiar with security, compliance, and disaster recovery in enterprise settings

● 沟通与协作
与产品、数据科学、业务与平台团队清晰沟通并推动落地
Strong communication and stakeholder management across product, data, business, and engineering

● 思维与工作方式
具备创造性解决问题能力、研究与分析型思维、细节导向；能适应节奏快、压力大的环境与快速变化
Creative problem‑solving, research/analytical mindset, detail‑oriented; thrives under fast pace and high pressure

● 语言
英语熟练，德语加分
Proficient English; German is a plus

经验要求（Experiences: 3-6 Years）

● 工程与平台
在软件工程、DevOps、平台工程或 AI/ML 平台开发与运营领域工作经验
Software engineering, DevOps, platform engineering, or AI/ML platform development & operations

● 跨团队领导
企业环境中带领跨职能团队设计、构建与运营大规模 AI 平台的经验
Leading cross‑functional teams to design, build, and operate large‑scale AI platforms in enterprise settings

● 云原生与容器
云原生架构、微服务、容器编排（Kubernetes / Docker） 实操经验
Cloud‑native architectures, microservices, and Kubernetes/Docker

● 分布式系统优化
性能监控、故障排查、优化与根因分析（RCA）经验
Performance monitoring, troubleshooting, optimization of distributed systems, incl. RCA

● 端到端 AI 交付
模型部署、生命周期管理、与业务应用集成的交付经验
Delivering end‑to‑end AI solutions (model deployment, lifecycle management, integration with business apps).

● 加分项
技术选型、供应商管理、平台项目预算规划经验（加分项）
Technology selection, vendor management, and budget planning for platform projects is a plus