Production Engineer, Network AI Lead

Meta•Menlo Park, CA

10d•$184,000 - $257,000

About The Position

The Network Infrastructure team designs, builds, and operates Meta’s global network, including backbone, data center, and AI network domains. Production Network Engineers combine software and network engineering to design, build, and operate the worldwide network across its lifecycle, from planning and product definition through design, quality assurance, deployment, and monitoring. In this role, you will develop and deploy network software, systems, and tools to maintain reliability, scalability, and efficiency. You will help solve network scaling challenges for Meta’s products and AI workloads by creating scalable designs, automation, and data-driven solutions. The role includes participating in an on-call rotation and contributing to team development through peer mentorship.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, a 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 such as Python, C++, Go, or Rust.
Experience learning software, frameworks, and APIs.
Experience configuring and maintaining network devices and network management systems, or applications such as web servers, load balancers, relational databases, storage systems, and messaging systems.
Experience developing and understanding network device configurations for at least one vendor, such as Juniper, Cisco, Arista, or Brocade.

Nice To Haves

Experience designing physical network infrastructure, including rack solutions, fiber connectivity, and automated design synthesis for AI or GPU cluster fabrics, ring interconnects, or backbone aggregation topologies.
Ongoing AI skill development, such as prompt or context engineering and agent orchestration, and staying current with emerging AI technologies.
Experience implementing responsible and ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Experience with centralized or hybrid routing design, including synthesis and verification frameworks for large-scale multiplanar or disaggregated network topologies.
Ability to integrate AI tools to optimize or redesign workflows and deliver measurable impact, such as efficiency gains or quality improvements.
Experience integrating AI-assisted workflows or automation tools to accelerate network design, testing, or operational processes with measurable efficiency or quality improvements.
Experience qualifying new network hardware platforms and optics through structured new product introduction frameworks, including end-to-end validation and targeted feature qualification.

Responsibilities

Establish and implement global best practices and design scalable network solutions.
Build and maintain automation and tools for product introductions, network deployment, release engineering, and operations.
Design and develop solutions that scale across network equipment hardware platforms.
Lead improvements to automation for continuous integration, validation, testing infrastructure, release, and configuration management across backbone, data center, and edge networks.
Collaborate with hardware, software, and sourcing teams to develop networking solutions and influence future networking infrastructure.
Investigate complex technical issues across networks, including tooling, hardware failures, and network problems.
Improve operational processes and implement them as scalable, automated workflows.
Identify operational roadblocks across peers and cross-functional teams, deliver automation solutions, and drive change.
Identify gaps affecting multiple teams, develop execution plans, lead projects, and influence other teams toward their goals.
Participate in an on-call rotation, learn from production challenges, and use those lessons to improve current and future products.
Support team growth and development through peer mentorship.