Network Engineering and Operation Manager

Zoom•San Jose, CA

8d•Hybrid

About The Position

This role leads global network infrastructure and data center operations supporting over 10,000 employees and AI/ML training infrastructure. The manager oversees a team of 13 globally distributed network engineers and data center technicians. The team is operating in a follow-the-sun model to provide continuous coverage, while partnering closely with the Network and Infrastructure Architects to execute strategic initiatives.

Requirements

Hold a BS/MS in Computer Science or equivalent experience.
Have 10+ years in network engineering with 5+ years managing distributed technical teams.
Be proficient in network operations best practices, network reliability and uptime, and deep Zero Trust security expertise.
Have hands-on experience with AI/ML infrastructure, high-performance networking, cloud interconnectivity, and network observability platforms.
Have proven experience leading large-scale infrastructure projects.
Willingness to participate in on-call rotation while maintaining both leadership responsibilities and hands-on technical involvement transforming a team.
Have excellent communication and stakeholder management skills with ability to influence without authority and translate complex technical concepts for executive stakeholders and non-technical audiences.

Responsibilities

Managing global network infrastructure with BGP and OSPF routing protocols.
Architecting cloud connectivity across AWS and GCP to ensure network reliability and uptime for users worldwide.
Implementing and maintaining Zero Trust network architecture in partnership with security architects. This includes identity verification, least-privilege access, micro-segmentation, and continuous authentication across network, data center, and cloud environments.
Collaborating with SOC and security teams on threat detection and vulnerability management, while developing comprehensive security policies for sensitive data flows and high-value assets.
Driving Lab, build and AI training infrastructure, providing high-performance, low-latency networks for GPU clusters supporting distributed ML workloads with 100+ GPUs.
Optimizing network topology for collective communications, managing storage networking for high-throughput data pipelines.
Overseeing data center operations supporting dense GPU deployments with specialized power and cooling requirements.
Coordinating megawatt-scale capacity planning and leads data center migrations while considering long-running training jobs.