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채용Microsoft

Principal Software Engineering Manager

Microsoft

Principal Software Engineering Manager

Microsoft

United States, Washington, Redmond

·

On-site

·

Full-time

·

1mo ago

필수 스킬

Azure

Overview:

Business Group Overview:

Within AI Platform, the Azure AI Search team powers rich knowledge base experiences for apps of all kinds. We integrate the best of Microsoft AI for content understanding, search relevance, and knowledge sources.

Job Purpose Overview:

As a Principal Software Engineering Manager, you will shape end-to-end customer and developer experiences for Azure AI Search—ensuring customers can discover, adopt, and succeed with AI capabilities at global scale. You will operate where product experience meets cloud services, setting direction that improves reliability, security, and time-to-value.

You will lead and grow a high-performing team that discovers, defines, and delivers new product capabilities—often turning ambiguous customer needs into clear, shippable features and reliable components. You will foster a high-trust environment where engineers collaborate, move quickly, and continuously raise the bar in a demanding and exciting space. You will also apply evolving AI tools and AI-assisted engineering practices to design, implement, test, and ship AI features faster and more safely across UX flows, portal experiences, samples, SDKs, and APIs.

You will thrive in a highly dynamic environment by staying close to users—listening, learning, and translating feedback into product and experience improvements. You will own key entry points and integration experiences (including partner integrations) so customers can onboard smoothly, extend the product confidently, and realize value quickly.

You will set technical direction and drive operational excellence from design through production—building for security, reliability, and observability, and ensuring features can be operated with confidence at scale. You’ll establish strong engineering systems (quality, incident readiness, and release practices) and use data from real-world usage to continuously refine the product experience.

Success in this role is measured by outcomes customers feel: simpler onboarding, clearer and more consistent experiences across every surface area, and secure, reliable features that run smoothly in production—enabling faster adoption of new AI capabilities. Success is also reflected in the team you build: a high-trust, high-performance culture that adapt

Responsibilities-
Leads the disciplined adoption and continuous improvement of AI tools and Responsible AI practices across the SDLC, ensuring accountability for AI-generated assets and using engineering health metrics to drive measurable process improvements and share learnings.

  • Leads engineering excellence for production services by driving diagnosability and incident prevention (debugging, telemetry, retrospectives), strengthening secure and privacy-preserving operations (least privilege), and raising code quality through timely, high-signal reviews, automated analysis, and best practices (including GenAI) to deliver secure, maintainable, high-performing code while proactively managing blockers and risks.

  • Managers deliver success through empowerment and accountability by modeling, coaching, and caring. Model: Live our culture. Embody our values. Practice our leadership principles. Coach: Define team objectives and outcomes. Enable success across boundaries. Help the team adapt and learn. Care: Attract and retain great people. Know each individual’s capabilities and aspirations. Invest in the growth of others.

  • Leads cross-group planning and execution (project/release/work management) by breaking long-term vision into milestones, driving estimation and capacity planning, and ensuring secure, compliant delivery with operational readiness (flighting, rollback, and disaster recovery).

  • Partners with internal and external stakeholders to validate user requirements and feasibility, incorporates customer insights and success metrics (including accessibility/globalization), and advocates for customer security and privacy needs across the solution.

Qualifications:

Minimum 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.

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

  • 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

  • 4+ years of people management experience, including hiring, coaching, performance management, and building high-trust, high-performing teams.

  • Experience owning end-to-end customer and developer experiences across one or more product surfaces including defining requirements and driving delivery.

  • Experience with distributed systems and production operations (reliability, incident response, observability/telemetry, and safe release practices).

  • Experience designing and delivering secure services, including identity/access patterns and privacy/compliance considerations.

  • Demonstrated use of AI-assisted engineering tools to improve SDLC quality and velocity, including responsible use of AI-generated assets

  • Strong customer empathy with a track record of using qualitative and quantitative feedback to iterate product experiences.

Software Engineering M5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 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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1

총 지원 클릭 수

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모의 지원자 수

0

스크랩

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Microsoft 소개

Microsoft

Microsoft

Public

Microsoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.

10,001+

직원 수

Redmond

본사 위치

$3000B

기업 가치

리뷰

3.8

5개 리뷰

워라밸

4.1

보상

4.3

문화

3.4

커리어

3.2

경영진

3.0

65%

친구에게 추천

장점

Excellent compensation and benefits package

Four-day workweek with improved work-life balance

Supportive managers and teams

단점

High-pressure environment causing anxiety

Unprofessional interview processes

Limited creative work opportunities

연봉 정보

5,620개 데이터

Senior/L5

Senior/L5 · Account Management

5개 리포트

$209,483

총 연봉

기본급

$181,941

주식

-

보너스

-

$194,895

$209,483

면접 경험

1개 면접

난이도

4.0

/ 5

소요 기간

14-28주

경험

긍정 0%

보통 0%

부정 100%

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit