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Lead design and implementation of a self-healing resource distribution ecosystem for cloud infrastructure, managing high-impact work across distributed systems, risk modeling, and policy enforcement. Requires a bachelor's degree in computer science or equivalent, eight years in software development, three years in technical leadership, eight years building large-scale infrastructure or distributed systems, and two years managing people. You'll coach engineers, set technical direction, and collaborate across multiple organizations.

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Job Description

  • Lead the design and implementation of a holistic, self-healing resource distribution ecosystem. Turn a big-picture goal into concrete projects for yourself and the team.
  • Operationalize the potential of Agentic Fleet Management. Lead the transition to artifact-motivated software development, ensuring that user intent is captured as structured artifacts to guide autonomous agents.
  • Manage high-impact challenges at the intersection of large-scale distributed systems, risk modeling, and policy enforcement. Design universal, high-level resource abstractions that operate above the level of a single data center.
  • Collaborate with partner teams across the Core Cloud Artificial Intelligence (C2ai) organization, ML Fleet, Site Reliability Engineering (SRE), and all Product Areas to define requirements and deliver a unified platform.
  • Coach and grow engineers on the team, build a strong leadership bench, while fostering a culture of technical excellence, strategic thinking, and innovation.

Minimum qualifications:

  • Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
  • 8 years of experience in software development and 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  • 8 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
  • 2 years of experience in a people management or team leadership role.

Preferred qualifications:

  • Proven ability to lead complex, cross-functional technical projects from conception to completion and drive technical strategy in a multi-stakeholder environment.
  • Familiarity with performance analysis, modeling, and tuning of complex systems, particularly in the areas of resource management.
  • Deeply technical Engineering Manager (EM) with a proven track record of stabilizing and growing high-impact teams.
  • Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
  • 8 years of experience in software development and 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  • 8 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
  • 2 years of experience in a people management or team leadership role.
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  • Role Engineering Manager, Google Cloud
  • Experience 5-7 years
  • Education Bachelor Degree, or equivalent experience
  • Work type On-site
  • Location India
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Google
AI Research Lab · 500+ Members · Mountain View, CA, United States

Google builds internet, software, cloud, and AI products used by consumers, developers, and organizations. Its portfolio includes Search, YouTube, Android, Chrome, Maps, Gmail, Workspace, Google Cloud, advertising platforms, devices, and Gemini AI products. The company develops large-scale computing infrastructure and research that power information retrieval, communication, productivity, media, navigation, and machine learning. Google is the largest operating business within Alphabet and earns a substantial share of its revenue from digital advertising.

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Job Overview
Eligibility
India Right to work in India required.
Workplace
On-site
Job Posted:
4 days ago
Job Type
Full Time
Education
Bachelor Degree, or equivalent experience
Experience
5-7 years

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