Meta is looking for a Network Deployment & Support Engineering lead to join the team responsible for planning and executing network deployments and migrations to build large-scale AI backbone network infrastructure. In this role, you will have a unique opportunity to work on cutting-edge Optical and IP networking technologies, owning the deployment planning, implementation, and scaling of Meta's AI network infrastructure.
Responsibilities
Drive strategic planning by building and executing six-month to multi-year roadmaps that support business growth and transformation. Balance high-level strategic vision with hands-on leadership to deliver results across a broad portfolio of initiatives
• Lead the technical strategy, architecture, and execution for team's projects within Edge Network Services (ENS) on network deployment and migrations, ensuring alignment with organizational vision and goals
• Collaborate cross-functionally across Network Engineering, Data Center, Edge, and planning teams to ensure the successful execution of shared goals on network capacity and reliability
• Provide technical contributions (design, deployment, migrate, etc.) on large-scale, complex programs at the experienced engineer's level, demonstrating domain expertise and technical impact
• Ensure high standards for reliability, scalability, and performance in all deliverables, driving continuous improvement in engineering processes and technical quality
• Deploy, migrate, and support our global production network, including edge, backbone, and data center infrastructure
• Manage key vendor relationships, including contract negotiations, pricing, and evaluation of current and potential partnerships
• Manage partner engineering team relationships to enable the team to effectively meet business needs
• Mentor and onboard new team members, raising the team's overall deployment capabilities and fostering team collaboration and knowledge sharing
• Demonstrate leadership behaviors by helping others, showing respect, connecting people, and driving collaboration within the team and the organization
• Travel required, approximately 10% to 30%
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
• 10+ years of Network Engineering, including hands-on responsibility for planning, building, deployment or migrating production network environments
• Experience with leveraging AI to drive areas of efficiency for improved reliability, quality, and speed of deployments
• In-depth experience with designing and deploying large-scale data center network infrastructure
• Knowledge of the data center design, construction, and startup/commissioning processes
• Experience leading cross-functional teams and driving large-scale data center projects
• Track record of defining technical strategy and delivering measurable outcomes on complex infrastructure projects
• Working knowledge of internet networking technologies (TCP/IP, routing, switching), and optical transport technologies
• Knowledge of enterprise and provider-level network hardware platforms (IP and Optical)
• Organizational, multitasking, prioritization, and communication experience
Preferred Qualifications
• Experience in leading and/or managing technical teams
• Data center design or relevant telecommunications certifications
• Knowledge of network tooling and automation systems
• Experience working on a global team in a matrixed environment with demonstrated ability to independently drive priorities and decisions
• In-depth knowledge of network protocols (TCP/IP, BGP, IS-IS, etc.)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
