Senior Production Network Engineer — Hyperscale & AI

Frankfort (KY)

On-site

USD 162,000 - 227,000

Full time

14 days+

Get more replies from employers

Send a job-specific resume in minutes.

Job summary

Meta's Production Network Engineering team designs and operates a global, large-scale network spanning data centers, edge points of presence, and backbone interconnects. You will drive strategy and execution across complex systems, mentor engineers, and apply AI-enabled workflows to improve reliability and performance.

The role requires 8+ years in production network engineering, deep knowledge of BGP/OSPF/IS-IS/MPLS, and Python automation experience.

Qualifications

Bachelor's degree in Computer Science, Computer Engineering or related field.
8+ years of experience in production network engineering for large-scale data centers or backbone networks.
Experience with routing protocols including BGP, OSPF, IS-IS, MPLS and large-scale Ethernet fabrics.
Experience developing and deploying network automation using Python or other scripting languages.
Experience leading cross-functional network reliability projects and incident response.

Responsibilities

Lead the design and delivery of large-scale production network projects spanning data center fabrics, backbone infrastructure, and edge network services
Define and drive the technical strategy and roadmap for network reliability, capacity, and operational efficiency across multiple teams
Develop and implement automation frameworks to reduce manual operational overhead and accelerate network design synthesis, network build and configuration management
Own cross-functional incident response and post-incident review processes, driving root cause analysis and systemic improvements to reduce recurrence
Identify and resolve complex network performance, routing, and reliability issues across multi-vendor, multi-protocol production environments
Collaborate with network architecture, capacity planning, and software engineering teams to align infrastructure investments with evolving AI and product demand forecasts
Establish and refine operational standards, runbooks, and monitoring frameworks to improve network observability and reduce mean time to detection and resolution
Contribute to organizational strategy by defining scalable approaches to network operations and influencing tooling and platform decisions across engineering teams
Mentor other engineers on network engineering best practices, operational discipline, and systems thinking across the production environment
Leverage AI-integrated workflows to accelerate network analysis, anomaly detection, and documentation, sharing learnings to scale adoption across the team