דרושים פרולוג'יק

In this role, you will collaborate with enterprise clients, customers, internal stakeholders, and cross-functional teams to quickly and accurately provision and integrate SecOps and other customer-managed security technologies.

Part of Google Cloud, Mandiant is a recognized leader in dynamic cyber defense, threat intelligence and incident response services. Mandiant's cybersecurity expertise has earned the trust of security professionals and company executives around the world. Our unique combination of renowned frontline experience responding to some of the most complex breaches, nation-state grade threat intelligence, machine intelligence, and the industry's best security validation ensures that Mandiant knows more about today's advanced threats than anyone.
Responsibilities
Oversee the security technology provisioning lifecycle for new and existing customers.
Develop technical implementation plans based on customer expectations and shared information.
Facilitate project management and technical support during onboarding. Collaborate closely with customers and internal teams.
Collaborate with customers to triage and implement remediations and recommendations.
Document all implementation details and collaboration meeting notes in the internal tracking system.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Responsibilities
Plan and execute detailed analysis of CPU workloads within the Google Cloud infrastructure, analyze trends and map future requirements.
Collaborate closely with architecture and modeling owners to understand design specifications and identify critical scenarios related to CPU performance and efficiency.
Develop and implement custom workload generation tools and methodologies to simulate real-world usage patterns on Google Cloud platforms.
Analyze the impact of machine learning applications on CPU usage, identifying opportunities for optimization and feature enhancements.
Lead the investigation and development of metrics to measure CPU performance and efficiency, presenting findings to stakeholders and contributing to strategic decisions.