Production Network Engineer

Meta; Richmond (VA); On-site; USD 162,000 - 227,000; Full time

Job summary

Meta's Production Network Engineering team designs and operates Meta's massive network spanning data centers, edge points, and backbone interconnects. This role drives strategy and execution, leading cross-functional initiatives to improve reliability and performance for AI workloads.

You will mentor engineers, build automation, and contribute to AI-integrated workflows to accelerate network analysis and remediation across the global production network environment.

Qualifications

• Bachelor's degree or equivalent practical experience in CS/engineering.
• 8+ years in production network engineering for large-scale data center or backbone networks.
• Experience with routing protocols and large-scale Ethernet fabrics in production.
• Experience developing network automation using Python for configuration/provisioning/monitoring at scale.
• Experience leading cross-functional network reliability projects, incident response, and remediation.
• Experience influencing technical decisions and network strategy across multiple teams.

Responsibilities

• Lead design and delivery of large-scale production network projects spanning data center fabrics, backbone, and edge services.
• Define and drive technical strategy for reliability, capacity, and efficiency across teams.
• Develop and implement automation frameworks to reduce manual overhead and speed design/build/configuration.
• Own cross-functional incident response and post-incident reviews, driving root cause analysis.
• Identify and resolve complex network performance, routing, and reliability issues across multi-vendor production environments.
• Collaborate with architecture, capacity planning, and software teams to align investments with AI/product demand.
• Establish and refine runbooks and monitoring to improve observability and MTTD/MTTR.
• Contribute to organizational strategy by scalable approaches to network ops and tooling decisions.
• Mentor engineers on best practices and systems thinking across production networks.
• Leverage AI-integrated workflows to accelerate analysis, anomaly detection, and documentation.

Skills

BGP

OSPF

IS-IS

MPLS

Ethernet fabrics

Python

AI tools integration

Cross-functional leadership

Incident response

Network reliability

Education

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Tools

Python

Job description

Summary:

Meta's global network infrastructure underpins billions of user connections and powers some of the world's most demanding AI and distributed computing workloads. The Production Network Engineering team is responsible for the design, deployment, operation, and continuous improvement of Meta's large-scale production network — spanning data centers, edge points of presence, and backbone interconnects. In this role, you will drive strategy and execution across complex network systems, lead cross-functional initiatives to improve reliability and performance, and apply deep subject matter expertise to solve problems at a scale few networks in the world match.

Required Skills:

Production Network Engineer Responsibilities:

1. Lead the design and delivery of large-scale production network projects spanning data center fabrics, backbone infrastructure, and edge network services

2. Define and drive the technical strategy and roadmap for network reliability, capacity, and operational efficiency across multiple teams

3. Develop and implement automation frameworks to reduce manual operational overhead and accelerate network design synthesis, network build and configuration management

4. Own cross-functional incident response and post-incident review processes, driving root cause analysis and systemic improvements to reduce recurrence

5. Identify and resolve complex network performance, routing, and reliability issues across multi-vendor, multi-protocol production environments

6. Collaborate with network architecture, capacity planning, and software engineering teams to align infrastructure investments with evolving AI and product demand forecasts

7. Establish and refine operational standards, runbooks, and monitoring frameworks to improve network observability and reduce mean time to detection and resolution

8. Contribute to organizational strategy by defining scalable approaches to network operations and influencing tooling and platform decisions across engineering teams

9. Mentor other engineers on network engineering best practices, operational discipline, and systems thinking across the production environment

10. Leverage AI-integrated workflows to accelerate network analysis, anomaly detection, and documentation, sharing learnings to scale adoption across the team

Minimum Qualifications:

1. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

2. 8+ years of experience in production network engineering, including design, deployment, and operations of large-scale data center or backbone network infrastructure

3. Experience with routing protocols and network technologies including BGP, OSPF, IS-IS, MPLS, and large-scale Ethernet fabrics in a production environment

4. Experience developing and deploying network automation using scripting or programming languages such as Python to manage configuration, provisioning, or monitoring at scale

5. Experience leading cross-functional network reliability or infrastructure projects, including driving incident response, root cause analysis, and systemic remediation

6. Experience influencing technical decisions and network strategy across multiple engineering teams through written proposals, design reviews, and stakeholder alignment

Preferred Qualifications:

1. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

2. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

3. Experience operating and troubleshooting networks at hyperscale, including multi-vendor spine-leaf data center fabrics and global backbone interconnects

4. Experience with network observability platforms, traffic engineering, and capacity modeling in high-throughput production environments

5. Experience integrating AI tools to redesign network operations workflows and deliver measurable improvements in efficiency or reliability outcomes

6. Familiarity with software-defined networking principles, network operating system internals, or co-development of network management platforms with software engineering teams

7. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Public Compensation:

$162,000/year to $227,000/year + bonus + equity + benefits

Industry:

Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Aff

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 [e-mail].