Technical Lead, Google Cloud Security

Google Google · Big Tech · Ramat Gan, Israel +1

Technical lead for Google Cloud Security, focusing on transitioning to an AI-native Security Operations Center (SOC). The role involves architecting an Agent Engine and universal APIs to enable enterprise security teams to orchestrate defense at machine speed, shifting from static workflows to multi-agent ecosystems.

What you'd actually do

  1. Lead the technical architecture and design for the Security Operations (SecOps) Security Orchestration, Automation, and Response (SOAR) Group.
  2. Drive the platform transition from bespoke playbooks to a AI-native SOC leveraging hybrid automation.
  3. Drive direction and technical leadership for the Response group teams, promoting a culture of engineering excellence that balances rapid development velocity with uncompromising code quality and system reliability.
  4. Provide overarching technical leadership, mentorship, and direction to a group of engineers building the multi-agent framework.
  5. Ensure reliability, scalability, and secure API governance across the universal agent marketplace and distributed systems.

Skills

Required

  • software development (Go, C++, Java, C# or Python)
  • software testing
  • software launching
  • software design
  • software architecture
  • machine learning (ML) design
  • ML infrastructure
  • model deployment
  • model evaluation
  • data processing
  • debugging
  • fine tuning

Nice to have

  • Master's degree or PhD in Computer Science or a related technical field
  • cybersecurity domain experience
  • SecOps experience
  • SOAR experience
  • SIEM platforms experience
  • AI/ML capabilities integration
  • Large Language Models (LLMs) integration
  • multi-agent orchestration frameworks integration
  • enterprise products integration
  • engineering best practices establishment
  • developer velocity improvement
  • mentoring engineers
  • API design
  • microservices architectures design

What the JD emphasized

  • AI-native SOC
  • Agent Engine
  • multi-agent ecosystems
  • machine speed defense
  • 5 years of experience with machine learning (ML) design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • Experience with designing and integrating AI/ML capabilities, Large Language Models (LLMs), or multi-agent orchestration frameworks into enterprise products.

Other signals

  • AI-native SOC
  • Agent Engine
  • multi-agent ecosystems
  • machine speed defense