IP Network Design Engineer, Long-Term Design & Delivery

The Meta Game, Inc.
Menlo Park, CA, United States
18 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Compensation
$184,000.0 - $257,000.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Border Gateway Protocol C++ (Programming Language) Code Review Computer Engineering Wavelength-Division Multiplexing Ethernet Networking Hardware Internet Protocol IPv4 IPv6 Multi-protocol Systems
+7 more
Python (Programming Language) Performance Tuning Migration Manager TCP/IP Juniper Information Technology Cisco

Job description

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., 2. Drive new-product introductions: define how and when to introduce them and the migration strategy across existing generations

  1. Design and drive large-scale migrations in live environments: MOPs, sequencing, risk assessment, de-risking without outages
  2. Own and evolve design rules, standards, and BOMs
  3. drive consensus on simplifications that make designs repeatable and cut delivery churn
  4. Deliver a clean product definition and design handoff to delivery/deployment partners
  5. 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
  6. Partner cross-functionally across Capacity Planning, Network Site sourcing, Network Fiber sourcing and represent designs in XFN reviews and drive decisions through influence
  7. Set technical direction for a domain and be the escalation point for complex design/topology problems
  8. Collaborate across regions (incl. EMEA/APAC), with flexibility for global-friendly hours, \~10-15% travel expected

Requirements

IP Network Design Engineer, Long-Term Design & Delivery Responsibilities:

  1. 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, 1. Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  2. Bachelor’s in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
  3. 6 years of experience in designing and/or operating large-scale IP networks
  4. Deep TCP/IP, IPv4/IPv6, and BGP (plus MPLS / IS-IS or similar) - configuration, typical patterns, performance tuning
  5. Understanding of 400/800G Ethernet and optical transport (DWDM) as it applies to backbone links and long-haul design
  6. Experience with network device configuration for at least one vendor (Juniper, Cisco, Arista, etc.)
  7. Coding in a higher-level language (Python / C++ / Go)
  8. Experience collaborating with cross-functional partners, resolving technical disagreements, and driving alignment across teams without direct authority, 1. Backbone/WAN experience in the context of hyperscalers
  9. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  10. Experience introducing new network platforms and driving cross-generation migrations at scale
  11. 10+ years of experience designing/operating backbone or large-scale IP networks
  12. Experience setting technical direction for a team of 3+ engineers
  13. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  14. Understanding of AI workloads and the demands they place on topology
  15. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  16. Familiarity with capacity-planning processes and physical constraints (cabling, space, power, fiber)

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