Production Engineer, Network AI Lead

Meta; Menlo Park (CA); On-site; USD 260,000 - 420,000; Full time

Job summary

Meta in Menlo Park seeks a Production Network Engineer to design, build, and operate our global network and AI backbones. You will contribute to scalable, reliable infrastructure and develop automation to keep the backbone fast and efficient.

The role blends software and networking, covering planning, deployment, QA, and monitoring. You will apply AI-driven workflows and validate hardware across multiple vendors in a highly collaborative environment.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
• 8+ years of relevant experience in developing scalable and reliable systems and/or networks.
• Experience coding in higher-level languages (e.g., Python, C++, Go, Rust, etc.).
• Experience learning software, frameworks, and APIs.
• 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 developing and understanding network device configuration for at least one vendor (Juniper, Cisco, Arista, Brocade, etc.).
• Experience with physical network infrastructure design including rack solutions, fiber connectivity, and automated design synthesis for AI or GPU cluster fabrics, ring interconnects, or backbone aggregation topologies.
• 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).
• Experience with centralized or hybrid routing design, including synthesis and verification frameworks for large-scale multiplanar or disaggregated network topologies.
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements).
• Experience integrating AI-assisted workflows or automation tooling to accelerate network design, testing, or operational processes with measurable efficiency or quality improvements.
• Experience qualifying new network hardware platforms and optics through structured NPI frameworks, including end-to-end validation and targeted feature qualification.

Responsibilities

• Design, build, and operate scalable and reliable networking systems for large-scale data centers and AI workloads.
• Develop and deploy network software, automation, and tooling to maintain high reliability and efficiency.
• Collaborate across planning, design, QA, deployment, and monitoring to deliver end-to-end network solutions.

Skills

Python

C++

Go

Rust

AI knowledge

Network automation

Data analytics

Problem solving

Communication

Education

Bachelor's degree in Computer Science/Engineering or equivalent

8+ years of relevant experience

Tools

Juniper

Cisco

Arista

Brocade

NMS systems

Web servers

Load balancers

Databases

Storage systems

Job description

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 data center network domain. We create new and innovative ways of designing and operating our global data center 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 key 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; to cutting-edge challenges in AI workloads that power new Meta products.

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
• 8+ years of relevant experience in developing scalable and reliable systems and/or networks
• Experience coding in higher-level languages (e.g., Python, C++, Go, Rust, etc.)
• Experience learning software, frameworks, and APIs
• 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 developing and understanding network device configuration for at least one vendor (Juniper, Cisco, Arista, Brocade, etc.)
• Experience with physical network infrastructure design including rack solutions, fiber connectivity, and automated design synthesis for AI or GPU cluster fabrics, ring interconnects, or backbone aggregation topologies
• 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)
• Experience with centralized or hybrid routing design, including synthesis and verification frameworks for large-scale multiplanar or disaggregated network topologies
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience integrating AI-assisted workflows or automation tooling to accelerate network design, testing, or operational processes with measurable efficiency or quality improvements
• Experience qualifying new network hardware platforms and optics through structured NPI frameworks, including end-to-end validation and targeted feature qualification