Senior Software Engineering Manager, Gce, Resource and Service Orchestration

Google Google · Big Tech · Sunnyvale, CA +2

Senior Software Engineering Manager for Google Compute Engine (GCE), responsible for directing the strategy, design, and execution of Zone and Cluster Services that manage compute resources at a global scale. The team's critical orchestrator services enable workloads from standard cloud instances to massive clusters supporting advanced AI models, including empowering customers using TPUs and GPUs at scale. The role involves leading and mentoring a distributed engineering team, defining technical roadmaps, overseeing system health, and partnering with Product Management and other infrastructure teams for AI and infrastructure innovations.

What you'd actually do

  1. Define the multi-year technical roadmap and architectural goal for Zone and Cluster Services managing Google Compute Engine (GCE) Resources. Drive innovations around AI Cluster Management, VM Core Services, and Instance Management.
  2. Lead initiatives to empower customers leveraging Tensor Processing Unit (TPUs) and Graphics Processing Unit (GPUs) at unprecedented scale with granular control over cluster configuration, scheduling, and management.
  3. Lead, mentor, and grow a high-performing distributed engineering team consisting of Staff Software Engineers, Software Engineering Managers, and Software Engineers across multiple geographic regions.
  4. Oversee system health, performance improvements, and critical initiatives such as Compute Disaster Recovery control plane automation to guarantee maximum uptime and recovery capabilities.
  5. Partner closely with Product Management, Capacity Planning, and other infrastructure teams to deliver reliable and efficient massive-scale AI and Infrastructure innovations.

Skills

Required

  • C++
  • Java
  • Python
  • Kotlin
  • Go
  • technical leadership
  • people management
  • team leadership

Nice to have

  • Master's degree or PhD in Computer Science or related technical field
  • managing distributed teams
  • leading managers or tech leads
  • large-scale cloud or infrastructure environment
  • building large-scale distributed systems
  • cloud service infra
  • cluster management technologies
  • large-scale AI/ML workloads
  • understanding of the AI/ML landscape

What the JD emphasized

  • managing compute capacity for advanced artificial intelligence models
  • AI Cluster Management
  • empower customers leveraging Tensor Processing Unit (TPUs) and Graphics Processing Unit (GPUs) at unprecedented scale
  • massive-scale AI and Infrastructure innovations

Other signals

  • managing compute capacity for advanced AI models
  • AI Cluster Management
  • empower customers leveraging TPUs and GPUs at unprecedented scale
  • massive-scale AI and Infrastructure innovations