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Salary
≈ $207k – $416k per year (Estimated)
Location
In office (Menlo Park)
Seniority
Staff · 10+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Aug 7, 2026. Meta scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Meta Platforms is an American technology company founded in 2004 as Facebook and renamed in 2021 to signal its investment in immersive computing. It operates the largest family of social and messaging applications in the world, comprising Facebook, Instagram, WhatsApp, Messenger and Threads, and earns almost all of its revenue from advertising sold against that audience. Headquartered in Menlo Park, California, the company also develops the open Llama language models and the Reality Labs division behind Quest headsets and Ray-Ban smart glasses.
Meta's backbone carries the traffic behind every product and, increasingly, the AI training and inference fabrics reshaping the network. The Long-Term Design & Delivery (LTD) team owns how that backbone evolves 2-3 years out: turning long-range traffic demand into the topology, designs, and technology introductions partnering with delivery orgs to execute. We're looking for a Production Network Engineer to lead IP design across our backbone domains.

Production Network Engineers at Meta are hybrid software and network engineers. While coding is a requirement for this role, the emphasis is design and de-risking at scale: defining multi-year topology plans, driving new-product introductions and migrations, and producing designs the delivery and deployment teams can build without churn.

Responsibilities

Own long-term IP backbone design for one or more domains or regions - translating business demand into topology, product definition and device selection 2-3 years ahead Drive new-product introductions: define how and when to introduce them and the migration strategy across existing generations Design and drive large-scale migrations in live environments: MOPs, sequencing, risk assessment, de-risking without outages Own and evolve design rules, standards, and BOMs; drive consensus on simplifications that make designs repeatable and cut delivery churn Deliver a clean product definition and design handoff to delivery/deployment partners Write and review code/automation for the entire design lifecycle: what-if analysis, BOM generation, hardware selection and partner with teams across the entire tooling-ecosystem Partner cross-functionally across Capacity Planning, Network Site sourcing, Network Fiber sourcing and represent designs in XFN reviews and drive decisions through influence Set technical direction for a domain and be the escalation point for complex design/topology problems Collaborate across regions (incl. EMEA/APAC), with flexibility for global-friendly hours, ~10-15% travel expected

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Bachelor's in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience 6 years of experience in designing and/or operating large-scale IP networks Deep TCP/IP, IPv4/IPv6, and BGP (plus MPLS / IS-IS or similar) - configuration, typical patterns, performance tuning Understanding of 400/800G Ethernet and optical transport (DWDM) as it applies to backbone links and long-haul design Experience with network device configuration for at least one vendor (Juniper, Cisco, Arista, etc.) Coding in a higher-level language (Python / C++ / Go) Experience collaborating with cross-functional partners, resolving technical disagreements, and driving alignment across teams without direct authority Backbone/WAN experience in the context of hyperscalers Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience introducing new network platforms and driving cross-generation migrations at scale 10+ years of experience designing/operating backbone or large-scale IP networks Experience setting technical direction for a team of 3+ engineers Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Understanding of AI workloads and the demands they place on topology Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Familiarity with capacity-planning processes and physical constraints (cabling, space, power, fiber)

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