微软
Principal Software Engineer--M365 Storage Team
Principal Software Engineer--M365 Storage Team
发布于 大约 8 小时前普通员工/个人贡献者
苏州市
高级经验
全职员工
仅现场办公
本科
后端开发
Ai-Native
低延迟
分布式系统
存储引擎
性能优化
数据库
高并发
AI 估算 · 40k–70k
Principal级别，存储领域专家，微软平台加成，苏州薪资水平较高
职位详情
关于这个职位
该职位负责微软M365存储团队的核心系统架构设计与开发，专注于大规模分布式存储、数据库和AI原生平台的现代化改造
作为Principal工程师，需要领导技术架构演进，优化性能与可靠性，并推动AI在工程实践中的深度应用
适合具有深厚系统编程背景和分布式系统经验的资深技术专家
最低要求
Required Qualifications:
Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python or equivalent experience.
Extensive industry experience building large-scale cloud services, distributed systems, storage platforms, or database systems.
Solid understanding of operating systems, memory management, threading, synchronization, networking, and I/O subsystems.
Expert knowledge of distributed system design and architecture.
Proven experience designing or operating large-scale storage and database platforms.
Solid understanding of storage engines, database internals, replication mechanisms, transaction processing, consistency models, fault tolerance, high availability architectures, and data durability strategies.
Experience with large-scale data platforms supporting mission-critical workloads.
Demonstrated success building systems that operate at hyperscale.
Experience designing and supporting high-concurrency architectures, low-latency services, and high-throughput systems, with expertise in service resiliency, performance tuning, capacity management, and production operations.
Ability to diagnose and resolve problems across complex distributed environments.
Solid interest and demonstrated experience applying AI to engineering workflows and product architectures.
Ability to critically evaluate emerging AI technologies and identify transformational opportunities.
Experience using AI-assisted development, design, diagnostics, automation, or operational workflows.
Passion for reimagining platforms and engineering systems through AI-driven innovation.
Exceptional analytical and problem-solving skills.
Ability to navigate ambiguity and drive clarity in highly complex technical domains.
Solid architecture review and design evaluation skills.
Proven influence across organizations without direct authority.
Excellent communication and collaboration skills with engineers, architects, product leaders, and executives.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
工作职责
System Architecture & Platform Leadership
Lead the architecture, design, and evolution of large-scale distributed storage, database, and data platform systems.
Drive modernization of critical platform components to support next-generation AI and Copilot workloads.
Re-architect legacy services and infrastructure using AI-native design principles.
Define long-term technical strategy and architectural direction across multiple services and teams.
Identify and eliminate architectural bottlenecks impacting scalability, reliability, performance, and operational efficiency.
Systems Programming & Performance Engineering
Design and implement highly efficient systems-level software in languages such as C++, Rust, C#, Go, or similar.
Drive end-to-end performance optimization across storage engines, networking, caching, concurrency control, and data access layers.
Solve complex challenges involving high concurrency, low latency, throughput optimization, and resource efficiency.
Lead root-cause analysis and resolution of difficult production issues involving distributed systems and storage infrastructure.
Establish engineering standards and best practices for performance-critical software development.
Storage & Database Innovation
Design and optimize storage engines, database architectures, replication technologies, indexing systems, and data management frameworks.
Lead innovation in areas such as:
High availability and disaster recovery
Data durability and consistency
Replication and synchronization
Metadata management
Query optimization
Storage efficiency and cost optimization
Intelligent caching and tiering
Drive architectural improvements that enable large-scale AI and retrieval-driven workloads.
AI-Native Transformation
Champion AI-native engineering practices across architecture, development, testing, and operations.
Apply AI-assisted approaches to system design, performance analysis, reliability engineering, and operational automation.
Identify opportunities to redesign products and platforms around emerging AI capabilities instead of incrementally enhancing legacy models.
Build frameworks and workflows that integrate AI into engineering decision-making and operational management.
Influence the organization's AI transformation strategy through thought leadership and technical innovation.
优先资格
Preferred Qualifications:
Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Experience building storage or database systems supporting AI, search, retrieval, vector, or large-scale analytics workloads.
Expertise in cloud-scale platforms such as Azure, AWS, or Google Cloud.
Experience with modern database technologies (distributed SQL, NoSQL, vector databases, or analytical engines).
Deep familiarity with observability, telemetry, reliability engineering, and automated operations.
Contributions to open-source systems, storage technologies, databases, or distributed computing frameworks.
Track record of leading major platform transformations with significant business impact.
AI 洞察
优缺点分析
优点
- 存储与AI结合的前沿方向，职业发展空间广阔
- 与全球顶尖工程师合作，技术视野和影响力提升
- 薪资福利优厚，工作稳定，WLB相对较好
- 对技术深度要求极高，需兼顾架构视野与代码实现
- 跨团队协作和影响力建设难度大，需具备沟通和说服力
- 生产系统问题复杂，可能面临高压排障和长期优化任务
- 适合有8年以上分布式系统经验、热爱底层技术、希望引领AI-Native架构转型的资深工程师
缺点 / 挑战
- 微软全球平台，参与超大规模云系统建设，技术挑战高
角色解读
- 技术专家路线：深耕存储与分布式系统，成为领域权威
- 架构师路线：向首席架构师或技术总监方向发展
- AI转型机遇：掌握AI-Native设计方法，引领平台智能化升级
- 领导大规模分布式存储与数据库系统的架构设计与演进
- 使用C++/Rust/C#/Go等语言实现高性能系统组件
- 推动AI-Native工程实践，将AI融入架构设计、性能与可靠性优化
- 主导复杂生产问题的根因分析和技术决策
- 精通C++/Rust/C#/Go等系统级编程语言
- 深入理解分布式系统原理，包括一致性、复制、容错等
- 熟悉存储引擎、数据库内核、缓存、并发控制等底层技术
- 具备大规模云服务的设计与运维经验，善于解决高并发低延迟问题
申请策略
- 了解微软Azure存储和M365的技术栈，准备相关场景方案
- 面试中展现系统设计能力与创新思维，强调AI-native理念
- 突出大规模分布式系统或存储数据库项目的架构设计和落地经验
- 强调性能优化、故障排查和高可用架构的具体案例
- 展示AI辅助开发或AI在工作流中应用的实际经验
- 提及开源贡献或技术影响力证据
- 补充或巩固Rust等现代系统语言技能
- 深入学习AI编程助手和AI驱动的运维工具
面试指南
- 使用STAR原则，结合具体项目数据，突出个人在架构决策和问题解决中的角色
- 对于系统设计问题，先明确需求与约束，再提出多方案对比，最后总结权衡
- 展示学习和探索能力，说明如何评估和引入新技术
- 请描述你设计过的最复杂的分布式存储系统，解决了哪些关键问题？
- 如何保证系统在高并发下的低延迟和高可用？
- 你如何将AI技术应用到系统架构或运维中？
- 当面临多个服务需要重构时，你如何确定优先级和推进？
- 解释存储引擎的写入路径和一致性模型，如何优化？
职位点评
79
综合评分
微软苏州Principal工程师，AI-native存储与分布式系统前沿，高薪高挑战，WLB未明确。
从薪资福利、成长空间、工作节奏和岗位方向综合评估，方便横向比较。
更适合这类人
适合追求技术前沿和职业成长、对高薪和稳定性有期待的资深工程师，对工作生活平衡有一般要求。
表现最好
成长发展
相对薄弱
使命价值
薪资福利80
成长发展92
工作生活70
使命价值65
薪资福利
80较高
微软提供有竞争力的薪资、福利和稳定性，虽未在JD中披露具体数字，但作为行业巨头具备较强吸引力。
薪资信号未披露（AI估算：40K-70K/月）
成长发展
92较高
职位聚焦AI-Native系统架构、存储与数据库前沿，技术挑战大，成长空间广阔，同时微软内部也提供丰富的学习资源。
技术前沿前沿/新兴技术
技术栈C++、Rust、分布式系统、存储引擎、数据库、AI、Azure
业务类型ambiguous
工作生活
70中等
微软苏州位置明确，通常工作生活平衡较好，但JD未说明弹性或远程政策，存在一定不确定性。
工作模式仅现场办公
办公地点未明确
加班情况未提及（无法判断）
使命价值
65中等
微软以'赋能全球每个人和组织'为使命，但该职位偏重技术实现，社会价值体现间接。
行业发展高速增长赛道
社会影响中性/一般
使命信号empower every person and every organization
创新程度积极采用新技术
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