招聘
必备技能
Python
Java
JavaScript
Kubernetes
Azure
Overview:
Are you a customer-obsessed, AI-curious problem-solver who thrives in an inclusive, collaborative global team? Join Engineering Operations (Eng Ops) – the organization driving operational excellence across the Microsoft Cloud to strengthen quality, reliability, security, and customer trust. As part of Eng Ops, you’ll design solutions that prevent issues before they happen, embed AI-powered automation, and turn signals into actions that deliver measurable customer impact. Our culture of empowerment, inclusion, and growth mindset defines how we work.
Azure Reliability is driving transformation to AI-powered operations by building scalable ML infrastructure that enables autonomous, reliable, and secure cloud systems. We are looking for candidates that can combine deep technical expertise in MLOps with a proven ability to deliver measurable business impact through continuous learning, policy-driven governance, and responsible AI practices. Additionally, experience in cloud infrstructure with strong hands on expertise in Kubernetes. Success in this role means advancing operational autonomy, quality, and security, while fostering collaboration and accountability across teams.
Every day, customers stake their business and reputation on our cloud. You can help #Eng Ops keep them secure, resilient, and ready.
This role will require a minimum of three days in office.
Responsibilities:
Responsibilities:
- Partner across multiple product groups to apply subject-matter expertise in distributed systems design practices, interactions between cloud technology layers and components, basic dependencies at scale, and the code that defines infrastructures.
- Lead by example and mentor others to produce extensible and maintainable code used across products.
- Develop and evangelize insights, best practices, and standards that can be applied to improve system, platform, and/or product development and operations across the business.
- Drive continuous improvements in the architecture, code, features, operations and comprehensive use scenarios of products by leveraging end-to-end technical expertise.
- Make improvements to the product fundamentals and architecture, share knowledge and code, always looking for ways to make what we build useful to multiple teams and products.
- Demonstrate end-to-end expertise in distributed systems design, interactions between cloud technology layers.
- Provide technical leadership in test maturity reviews, static analysis reviews, meetings, on-call rotations, and incident responses throughout product development and operations cycles.
- Provides deep business and technical expertise as required to resolve major incidents.
Qualifications:
Required qualifications:
- Bachelor's Degree in Computer Science, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
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.
Preferred Qualifications:
- Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with Kubernetes and 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 8+ years technical engineering experience with Kubernetes and coding in languages including, but not limited to, Golang, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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关于Microsoft

Microsoft
PublicMicrosoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.
10,001+
员工数
Redmond
总部位置
$3000B
企业估值
评价
3.8
5条评价
工作生活平衡
4.1
薪酬
4.3
企业文化
3.4
职业发展
3.2
管理层
3.0
65%
推荐给朋友
优点
Excellent compensation and benefits package
Four-day workweek with improved work-life balance
Supportive managers and teams
缺点
High-pressure environment causing anxiety
Unprofessional interview processes
Limited creative work opportunities
薪资范围
5,620个数据点
Senior/L5
Senior/L5 · Account Management
5份报告
$209,483
年薪总额
基本工资
$181,941
股票
-
奖金
-
$194,895
$209,483
面试经验
1次面试
难度
4.0
/ 5
时长
14-28周
体验
正面 0%
中性 0%
负面 100%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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