Network Production Engineering, Infrastructure
Meta· enterprise· Social Media· Jul 13, 2026 · 4mo agoPosted 106 days ago
Menlo Park, CA
In office
Full-time
Senior
$145K–$185K est.
6+ years exp
Before you apply
Ghost Signal:
Open since July 13, 2026 — 106 days, and still accepting applications.
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.
Production Network 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 scaling challenges supporting billions of people using our family of apps, as well as cutting-edge challenges in AI workloads that power new Meta products.
Establish and implement global best practices and design new scalable network solutions Conceptualize, build, and maintain automation and tools to support 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 Be on-call to learn from real world production challenges and take the lessons to improve current and future generation products Help increase operational efficiency between peers and cross-functional teams by identifying roadblocks, designing and delivering automation solutions, and driving change Develop operational process improvements and implement them in scalable, automated workflows to enhance operational efficiency Proactively identify gaps that impact multiple teams, develop execution plans, drive projects to completion, and influence cross-functional teams to achieve shared goals
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 6+ years of experience with planning, designing, building and/or operating scalable systems/networks 4+ years of coding experience in at least one programming language (e.g. Python, Go, C++, or Java), and with willingness to learn new development languages as needed 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.) Hardware evaluation and vendor management Experience developing software using AI models 4 years experience in network automation software leveraging software defined networking principles 4+ years of experience in routing and switching - hardware design and knowledge of forwarding and data planes Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Network design experience, Traffic engineering and capacity planning in multifaceted networks Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) 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) Working knowledge of physical infrastructure design including structured cabling and fiber-optic cabling Experience managing multiple projects simultaneously and deliver against deadlines
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Keywords to mirror
aipythongojava
- Platform
- meta
- Effort
- medium