Network Engineer, Engineering R&D Environments

Meta's Lab Infrastructure, Network, Compliance, and Security (LINCS) team is seeking a network engineer to help build and scale the network infrastructure supporting Meta's global engineering labs. Our team is responsible for network design, deployment, and operations for Meta's global engineering labs where we support multiple engineering teams. With the importance of rapidly maturing new technologies like the Metaverse and Gen AI, there are significant opportunities to re-think traditional networking and iterate quickly in our environment. This role offers an opportunity to work directly with engineering teams that are maturing new hardware and software on the path to production.Network Engineer, Engineering R&D Environments Responsibilities:Own end-to-end frontend and backend network design, deployment, and operations for AI and compute lab clustersServe as a primary networking point of contact for backend fabrics, including Arista- and internally developed network OS-based scale-out networks supporting AI workloadsDesign, deploy, and support high-throughput, low-latency cluster networking, including congestion management (PFC/ECN), RDMA validation, and lossless transportPerform hands-on troubleshooting and root-cause analysis across L1–L4 using packet captures, telemetry, and vendor tools to resolve complex lab issuesSupport silicon, hardware, and software bring-ups, ensuring reliable connectivity and on-time validationLead and execute lab network lifecycle activities, including upgrades, migrations, capacity expansions, and decommissioning across regionsDevelop and maintain network automation, configuration templates, and zero-touch provisioning (ZTP) workflowsCreate and maintain MOPs, runbooks, and readiness checklists for internal teams and vendor executionsProvide direct consultation and training to cross-functional partners, enabling teams to operate and troubleshoot lab networksEnd-to-end ownership of projects from requirements definition through customer handoffCollaborate closely with hardware, software, systems, and lab operations teams to validate new platforms, optics, and network designsSupport limited travel (about 10%) for critical lab builds, migrations, or escalationsMinimum Qualifications:Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experienceBachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience6+ years of experience designing, deploying, and operating network infrastructure in production or lab environmentsExperience working in multi-vendor environments, including Arista, FBOSS-based platforms, and lab networking hardwareExperience with configuration management, code repositories, and zero-touch provisioning (ZTP) for network infrastructureExperience with IPv4/IPv6, L2/L3 protocols, including STP, OSPF, BGP, TCP/IP, DHCP, DNS, VLANs, VRRP, LACP, MC-LAG, ACLs, MACsec, and EVPN/VXLANWorking knowledge of scripting or programming languages (e.g., Python, shell) for automation and toolingDemonstrated experience to operate consistently while working under your own initiative, seeking feedback and input where appropriate in a global, time-critical environment, managing multiple priorities and mission-critical timelinesPreferred Qualifications:Understanding of physical infrastructure design, including structured cabling, space, power, and cooling systemsExperience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy review)Networking L1 expertise in validating multi-vendor optics, with proficiency using the BCM shell and I2C utilities to troubleshoot hardware-level issuesExperience with network automation, CI/CD pipelines, audit frameworks, and validation toolingHands-on experience with backend cluster networking, including scale-out fabrics, RDMA networks, and congestion managementExperience supporting AI/ML or high-performance compute clusters in lab or pre-production environmentsHands-on experience with lab test equipment, optics qualification (e.g., 400G/800G), optical switches and physical infrastructureExperience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)Hold networking certifications such as CCIE, JNCIE or equivalentDemonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologiesDemonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)Hands-on experience with disaggregated networking products and software, such as Meta's open network OS (FBOSS), SONiC, Cumulus Linux, or equivalent open networking platformsAbout Meta:Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.$135,000/year to $191,000/year + bonus + equity + benefitsIndividual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.