Wireless Network Engineer - Enterprise Infrastructure

The Enterprise Network Engineering team is responsible for designing, building, and operating one of the largest enterprise networks in the world. Networking is at the core of all Meta products and experiences, and we are looking for wireless network engineers who are interested in solving complex technical challenges in enterprise wireless across offices, retail spaces, data centers, and authentication services domains. The scale of the network and its continuous expansion presents an opportunity to work on and to solve interesting engineering challenges. We constantly push the boundaries of what is possible. We create new and innovative ways of designing and operating our networks and do it at scale with efficiency.

Responsibilities

Design, standardize, and manage wireless networks across a fleet of geographically distributed retail locations, ensuring consistency, scalability, and alignment with business requirements Contribute to engineering design, solution development, and ongoing management of a multi-vendor enterprise WiFi network infrastructure Perform wireless site surveys, RF spectrum analysis, and post-deployment validation to ensure optimal coverage, capacity, and performance in retail environments with high-density client usage Configure and manage wireless network controllers, access points, and related infrastructure components from vendors such as Cisco, Meraki, Aruba, or Juniper Mist Troubleshoot and resolve complex wireless connectivity issues, including RF interference, roaming failures, authentication problems, and throughput degradation Partner with InfoSec teams to design and continuously deliver security-related enhancements across retail and enterprise wireless environments Partner with facilities and remote site engineering teams to plan wireless infrastructure for new office builds, renovations, and campus expansions Partner with network operations and deployment teams to analyze data and performance metrics to improve reliability and resiliency of the wireless network Develop and maintain low-level design templates and deployment guides for third-party installers executing store buildouts and refreshes Develop automated methods to mitigate and remediate network events and minimize operational complexity Develop automation and tooling to proactively detect, mitigate, and remediate network events and minimize operational complexity across the retail fleet

Qualifications

3+ years of experience with 802.11 wireless standards, 802.1X authentication, and unlicensed radio frequency planning across 2.4 GHz, 5 GHz, and 6 GHz spectrum 3+ years of experience with Layer 2/Layer 3 networking fundamentals, including switching, VLANs, and routing as they relate to wireless network integration 2+ years of experience working with enterprise network OEM hardware (Cisco/Meraki, HPE/Aruba, Juniper Mist, Arista) 2+ years of experience with wireless design and survey tools (e.g., Ekahau, AirMagnet, or equivalent) 2+ years of experience with programming or scripting (Python, Bash, or similar) to automate network operations or build tooling Demonstrated knowledge of TCP/IP, IPv4 and IPv6, and related network services (e.g., DHCP, DNS, NTP) Experience with the Meraki cloud-managed platform, including RF profiles, Auto RF tuning, group policies, and fleet-wide template management across distributed retail sites Hands-on experience designing, configuring, and optimizing WiFi networks with knowledge of RF design and latest 802.11 standards (Wi-Fi 6E/7) Detailed understanding of tooling and automation to configure, manage, and operate networks at scale (e.g., Meraki APIs, Python) Demonstrated knowledge of controller-based and controllerless enterprise wireless architectures, monitoring systems, and RADIUS infrastructure Cisco Meraki Solutions Specialist or CCIE Wireless or an equivalent certification is preferred Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)