
Organizing the world's information and making it universally accessible.
Senior Software Engineering Manager, Natural Language for Databases
About the job
The Natural Language for Databases team's overall mission is to transform Cloud Databases for Agentic AI. We are at an inflection point where model capability and agentic software architectures have unleashed a revolution. Agents have become the predominant builders of applications which use databases and agents are increasingly also the users of these databases, displacing conventional applications. Our team's mission, in partnership with the wider Data Cloud organization, is to build the common platforms and frameworks needed to support agents on all databases.
The Natural Language team focuses on the automated translation of natural language into formal database queries so that agents can make full use of enterprise data, accurately and securely. This domain combines cutting edge ML research, novel agentic architectures, deep database understanding and scalable platform engineering to unlock natural language access to all of our Cloud Databases.The US base salary range for this full-time position is $262,000-$365,000 + 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
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Deliver the industry's leading platform for empowering agents to use enterprise data. This is a top priority for a business unit of Google Cloud.
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Develop a team of exceptionally strong software engineers, helping them to grow while navigating a fast-evolving, high stakes environment.
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Provide cross-organizational leadership, interfacing with product, research, UX, program management and executive leadership. Expect regular engagement at Vice President level.
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Balance the need for ongoing, open-ended research at the frontiers of AI and databases with the practical imperative to ship products and features that meet customers demands today.
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Employ deep technical expertise and exceptional judgement to guide the team through uncharted technical challenges and complex multi-stakeholder tradeoffs.
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 a people management or team leadership role.
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2 years of experience with GenAI techniques (e.g., Large Language Models, Multi-Modal, Large Vision Models) or with GenAI-related concepts (Language Modeling, Computer Vision).
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Experience building and deploying generative AI agents.
Preferred qualifications
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Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
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5 years of experience working in a complex, matrixed organization.
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Experience with Google Cloud Databases and other Google Cloud Platform (GCP) service.
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Experience with large-scale distributed databases, data warehouses, lakehouses and similar architecture.
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Experience with semantic modeling, graph databases and knowledge graphs.
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关于Google

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
员工数
Mountain View
总部位置
$1,700B
企业估值
评价
10条评价
4.5
10条评价
工作生活平衡
3.2
薪酬
4.3
企业文化
4.1
职业发展
4.2
管理层
3.8
82%
推荐率
优点
Great benefits and perks
Innovative and interesting work
Career development and learning opportunities
缺点
High pressure and expectations
Long hours and heavy workload
Fast-paced and overwhelming environment
薪资范围
57,503个数据点
Mid/L4
Mid/L4 · Accessibility Analyst
1份报告
$214,500
年薪总额
基本工资
$165,000
股票
-
奖金
-
$214,500
$214,500
面试评价
9条评价
难度
3.4
/ 5
时长
14-28周
录用率
44%
体验
正面 0%
中性 56%
负面 44%
面试流程
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
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