Network Production Engineer, Design

About the role

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• Network Production Engineer, Design
• Network Production Engineer, Design
• Denver, CO +3 locations
• Network Engineering
• + 2 more

The Network Infrastructure team is responsible for designing, building, and operating one of the largest networks in the world. Networking is at the core of all Meta products and experiences, and we are looking for Network Production Engineers who are interested in solving complex technical challenges in the Backbone, Datacenter, and AI Network domains.

The scale of the network and its continuous expansion presents an opportunity to work on and solve interesting engineering challenges in the datacenter network domain. We create new and innovative ways of designing and operating our global datacenter networks and do it at scale with efficiency.

Production Network Engineers at Meta are hybrid software and network engineers who design, build, and operate our worldwide network. This team owns the complete lifecycle of the network, which includes areas of planning, design, product definition, QA, deployment, and monitoring. Simple, elegant, and scalable network design, automation, and data analytics are the keys to meeting our demands.

In this role, you will be part of a team that is responsible for conceiving design solutions, developing and deploying network software, systems, and tools that keep the network operating at maximum reliability, scalability, and efficiency.

This role offers an opportunity to solve the scaling challenges of supporting billions of people using our family of apps, as well as to tackle cutting-edge challenges in AI workloads that power new Meta products.

Network Production Engineer, Design Responsibilities

• Establish and implement global best practices and design new scalable network solutions
• Conceptualize, build, and maintain automation and tools to support New Product Introductions, network deployment, release engineering, and operations
• Design and develop solutions that scale across a variety of hardware platforms of network equipment
• Lead enhancements of automation for continuous integration, validations, testing infrastructure, release, and configuration management across our global backbone, data center, and edge networks
• Work closely with our hardware, software, and sourcing teams to develop new networking solutions and influence the future of networking and its associated infrastructure
• Conduct thorough investigations into complex technical issues across networks, ranging from automated tooling to hardware failures and network issues
• Develop operational process improvements and implement them in scalable, automated workflows to enhance operational efficiency
• Help increase operational efficiency between peers and cross-functional teams by identifying roadblocks, designing and delivering automation solutions, and driving change
• Proactively find gaps that impact multiple teams, come up with the execution plan, drive the project, and influence other teams to reach their goals
• Participate in an on-call rotation to learn from real-world production challenges and take the lessons to improve current and future generation products
• Contribute to team growth and development through peer mentorship

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 8+ years of relevant experience developing scalable and reliable systems and/or networks
• Experience coding in higher-level languages (e.g., Python, C++, Go, Rust, etc.). Experience in learning software, frameworks, and APIs
• An engineering degree, or a related technical discipline, or equivalent experience
• Experience in the configuration and maintenance of network devices and NMS systems, or applications such as web servers, load balancers, relational databases, storage systems, and messaging systems
• Experience in developing and understanding network device configurations for at least one vendor (Juniper, Cisco, Arista, Brocade, etc.)

Preferred Qualifications

Strong understanding of network hardware, optics and fiber connectivity products including tradeoffs between different hardware architectures

Understanding of Physical Network Infrastructure including rack solution design, inter-rack and intra-rack fiber connectivity design, including automation of design synthesis to design and deliver Physical Design Plans (PDPs) for complex backend and frontend network topologies, including AI/GPU cluster fabrics, ring interconnects, and backbone aggregation layers

• Ability to collaborate cross-functionally with deployment and operations teams to resolve BOM variances, validate configurations, and deliver production-ready network builds on aggressive timelines
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Ability to develop and maintain fiber connectivity solutions using automation tools, ensuring data integrity across design-to-deployment pipelines and streamlining workflows between design systems and infrastructure databases
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Ability to leverage AI-assisted workflows to accelerate design population, automate testing, and innovate tooling—measurably improving quality and delivery speed
• Strong understanding of routing protocols and routing design including design synthesis and verification frameworks. Ability to deploy centralized and hybrid routing solutions
• Ability to with NPI teams to drive NPI qualification for new network platforms and optics, applying a principled framework to determine testing depth—from full end-to-end validation to targeted feature qualification
• Strong understanding of network topologies including scale-out and scale-up fabrics, multiplanar solutions, disaggregated solutions and their tradeoffs including high-level and low-level topological and configuration design artifact rendering
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

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