Senior Software Engineering Manager, Gdc Platform Operations

Google Google · Big Tech · Bengaluru, Karnataka, India

This role is for a Senior Software Engineering Manager at Google Cloud, focusing on Google Distributed Cloud (GDC) Platform Operations. The manager will lead teams responsible for transforming GDC's operations to be fast, reliable, autonomous, and unified with Google Cloud Platform. This includes setting team priorities, developing technical roadmaps, overseeing system designs, and managing engineers. The role involves building AI-native, agentic workflows for hardware ordering and deployment, ensuring efficient operations across connected and air-gapped fleets, and supporting AI-led services like computer vision and edge inferencing.

What you'd actually do

  1. Transform GDC's Day 0, 1, and 2 operations to be fast, reliable, autonomous and unified with Google Cloud Platform (GCP) experience. Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
  2. Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
  3. Develop the long-term technical direction and roadmap within, and often beyond, the scope of your teams.
  4. Oversee systems designs within the scope of the broader area, and review product or system development code to solve ambiguous problems.
  5. Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).

Skills

Required

  • C++
  • large-scale infrastructure
  • distributed systems
  • networks
  • compute technologies
  • storage
  • hardware architecture
  • technical leadership
  • people management
  • team leadership

Nice to have

  • systems engineering practices
  • incident response
  • monitoring
  • service-level objectives
  • change management
  • Machine Learning Infrastructure
  • Distributed Cloud/On-Premise
  • production operations for isolated systems
  • air-gapped systems

What the JD emphasized

  • AI-led Services
  • AI-native, agentic workflows
  • Google AI edge inferencing
  • complex, matrixed organization
  • production operations for isolated systems
  • air-gapped