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About the job
As a Software Engineering Manager within the Kubernetes Kernel team, you will initially lead the Kubernetes Config Connector (KCC) team and oversee the technology that ensures our high-scale customers achieve compliance and manage their infrastructure with production-grade reliability. You will define the KCC long-term goal, focusing on its role as a foundation for AI Agentic infrastructure, and accelerate resource coverage to unblock the next generation of Google Cloud users.
In this role, you will define and execute the strategy for KCC, focusing on improving core reliability (e.g., high availability/disaster recovery, safer upgrades) and addressing critical customer escalations. You will lead the team's effort to leverage LLMs and AI Agents via tools like the Open Source Software (OSS) repo-agent to automate the full resource lifecycle. This includes driving innovation in AI-powered code generation, automated code review, streamlined release processes, and intelligent support remediation to reach coverage goals. You will shape the product roadmap to evolve KCC's core infrastructure, meeting customer demands for continuous reconciliation and strict compliance. You will manage a team of Engineers, cultivating an environment of psychological safety, high execution, and continuous innovation. You will grow at the intersection of systems engineering, Infrastructure as Code (IaC), and Kubernetes. You will be creating production-grade systems that manage Google Cloud infrastructure on behalf of the user.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Lead the technical goal and execution for Kubernetes Config Connector, ensuring KCC evolves to meet critical customer demands for continuous reconciliation, compliance, and day two operations.
Minimum qualifications
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Bachelor’s degree or equivalent practical experience.
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8 years of experience in software development.
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5 years of experience in distributed cloud computing including 3 years of experience in containerization, container orchestration, or operations management.
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3 years of experience in a technical leadership role.
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2 years of experience in a people management or team leadership role.
Preferred qualifications
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Master's degree or PhD in Computer Science or a related technical field.
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5 years of experience in a people management or team leadership role.
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3 years of experience working in a complex, matrixed organization.
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Experience with KCC or other Kubernetes-native Infrastructure as Code (IaC) solutions like crossplane.
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Experience leading AI-driven development initiatives for IaC or cloud-native tooling.
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Google 소개

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
직원 수
Mountain View
본사 위치
$1,700B
기업 가치
리뷰
3.7
25개 리뷰
워라밸
3.8
보상
4.2
문화
3.4
커리어
3.9
경영진
2.8
68%
친구에게 추천
장점
Excellent compensation and benefits
Smart and talented colleagues
Great perks and work flexibility
단점
Management and leadership issues
Bureaucracy and slow processes
Constantly changing priorities and reorganizations
연봉 정보
57,502개 데이터
Junior/L3
L3
L4
L5
L6
L7
L8
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Junior/L3 · Data Scientist L3
0개 리포트
$176,704
총 연봉
기본급
-
주식
-
보너스
-
$150,298
$203,110
면접 경험
9개 면접
난이도
3.4
/ 5
소요 기간
14-28주
합격률
44%
경험
긍정 0%
보통 56%
부정 44%
면접 과정
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
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