Technical Program Manager, Network Solutions and Automation

Google Google · Big Tech · Singapore

Technical Program Manager focused on leading the end-to-end technical strategy, design, and delivery of internal tools, automation frameworks, and intelligent agents (AI/LLM-driven) for network infrastructure challenges. The role involves collaborating with technical teams to identify and automate manual network operations.

What you'd actually do

  1. Lead the end-to-end technical strategy, design, and delivery of internal tools, automation frameworks, and intelligent agents (AI/LLM-driven) aimed at diagnosing and resolving complex network challenges.
  2. Identify high-friction, repetitive, or error-prone manual network operations and lead cross-functional initiatives to replace them with automated workflows, minimizing operational overhead.
  3. Collaborate with internal business and cross-functional networking technical teams to identify and define tactical and strategic initiatives necessary to meet Google's network infrastructure needs for both expansion and cost optimization across Asia.
  4. Partner closely with network engineering, infrastructure, and software teams to deeply understand core networking challenges and translate them into actionable software requirements and tooling specs.
  5. Communicate progress internally and collaborate with other technical teams to track timeline and dependencies of infrastructure turn-up.

Skills

Required

  • technical program management
  • artificial intelligence/machine learning projects, tools or infrastructure
  • AI/machine learning projects, tools, or infrastructure with applications

Nice to have

  • networking
  • Python
  • R
  • data science
  • machine learning
  • intelligent agent
  • prototyping
  • cross-functional project management

What the JD emphasized

  • artificial intelligence/machine learning projects, tools or infrastructure
  • AI/machine learning projects, tools, or infrastructure with applications
  • intelligent agents

Other signals

  • AI/LLM-driven intelligent agents
  • automation frameworks
  • diagnosing and resolving complex network challenges
  • automated workflows