Job Description

The Network Infrastructure team is responsible for designing, building, and operating one of the largest networks in the world. Networking is at the core of all Meta products and experiences, and we are looking for Network Production Engineers who are interested in solving complex technical challenges in the Backbone, Datacenter, and AI Network domains.

The scale of the network and its continuous expansion presents an opportunity to work on and solve interesting engineering challenges in the datacenter network domain. We create new and innovative ways of designing and operating our global datacenter networks and do it at scale with efficiency.

Network Production Engineers at Meta are hybrid software and network engineers who design, build, and operate our worldwide network. This team owns the complete lifecycle of the network, which includes areas of planning, design, product definition, QA, deployment, and monitoring. Simple, elegant, and scalable network design, automation, and data analytics are the keys to meeting our demands. In this role, you will be part of a team that is responsible for conceiving design solutions, developing and deploying network software, systems, and tools that keep the network operating at maximum reliability, scalability, and efficiency.

This role offers an opportunity to solve the scaling challenges of supporting billions of people using our family of apps; to cutting-edge challenges in AI workloads that power new Meta products.

Responsibilities
Conceptualize, build, and maintain automation and tools to support New Product Introductions, network deployment, release engineering and operations
* Conduct thorough investigations into complex technical issues across networks, ranging from automated tooling to hardware failures and network issues
* Help increase operational efficiency between peers and cross-functional teams by identifying roadblocks, designing and delivering automation solutions, and driving change
* Proactively find gaps that impact multiple teams, come up with the execution plan and drive the project and influence other teams to reach there
* Design and develop solutions that scale across a variety of hardware platforms of network equipment
* Lead enhancements of automation for continuous integration, validations, testing infrastructure, release, and configuration management across our global backbone, data center, and edge networks
* Develop operational process improvements and implement them in scalable, automated workflows to enhance operational efficiency
* Participate in an on-call rotation with the rest of the team
* Hardware evaluation and vendor management

Qualifications
Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
* 2+ years of experience with planning, designing, building and/or operating scalable systems/networks
* 2+ years of coding experience in at least one programming language (e.g. Python, Go, C++, or Java), and rapidly learning new development languages
* Demonstrated knowledge of TCP, IPv4/6, Routing Protocols (one or more of BGP, MPLS, ISIS, or similar), and related network services (e.g. DHCP and DNS)
* Experience developing and understanding network device configuration in multi vendor environments (Juniper, Cisco, Arista, Brocade, etc.) 2+ years experience in network automation software leveraging software defined networking principles
* Network design experience and capacity planning in multifaceted networks
* Experience managing multiple projects simultaneously and delivering against deadlines
* Experience with modern data center architectures (spine-leaf, fabric)
* Experience working in global team environments to solve problems
* Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
* Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
* Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)