Meta
Network Engineer, Foundation & Support (Edge and Network Services Product Lifecycle Support)
$135K–$191K
Denver, CO +2 · Full-time · Posted Oct 14, 2026
- Location
- Denver, CO
Reston, VA
Menlo Park, CA - Experience
- 6+ years in network engineering; 6+ years designing, deploying, and operating LAN, WAN, and wireless networks at scale. The posting also requests experience across network hardware development lifecycle stages and leading large cross-functional projects.
- Education
- Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
About the job
Supports introduction and operational readiness of network platforms, cabling, and rack-integration products for Meta’s global data centers and edge infrastructure, including integrated AI systems.
What you'll do
- Validate operational readiness for new network platforms, topologies, cabling, and passive rack-integration products across server, rack, and multi-rack levels.
- Improve NPI processes, deployment and operations documentation, and technical references; communicate readiness risks and escalations.
- Coordinate with engineering, site operations, facilities, vendors, and other partners to align product readiness and deployment strategies.
What they ask for
- Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- 6+ years of network engineering experience focused on enterprise network deployment, operations, and site services infrastructure.
- 6+ years designing, deploying, and operating LAN, WAN, and wireless networks at scale across multiple physical sites.
- Experience with data center structured cabling and fiber-optic infrastructure; rack-level integration; network troubleshooting; automation; and NPI projects.
Pay
$135,000/year to $191,000/year (base salary)
Tools
Python, TCP, IPv4/6, LAN, WAN, wireless, NICs, optical transceivers
AI focus
Integrate AI tools to optimize or redesign workflows and deliver measurable impact; develop skills such as prompt/context engineering and agent orchestration; apply responsible AI practices, including risk assessment, bias mitigation, and quality and accuracy reviews.
Model-written summary · the original posting is authoritative