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Verified from career page · Posted 1w ago

Meta

Network Production Engineer, Network.AI

Meta · Facebook, Infrastructure, Network Engineering, Production Engineering

London

Mid-level

Machine learningCI/CDC++Distributed systemsJavaPythonRust

Last seen 5d ago

Posted
1w ago

Posted on 22 September 2026

Workplace
Not specified

Work model not stated

Salary
Not disclosed

Salary range not shared by the company

Visa sponsorship
Not specified

Visa sponsorship details unknown

This role has closed 5d ago ago. It's kept as a record — see Meta's open roles or the similar live roles below.

See Meta's open roles

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 scaling challenges supporting billions of people using our family of apps, as well as cutting-edge challenges in AI workloads that power new Meta products.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 identify gaps that impact multiple teams, develop execution plans, drive projects to completion, and influence other teams to align on solutions

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

6+ years of experience planning, designing, building, and/or operating scalable and reliable systems and/or networks

Experience coding in at least one programming language (e.g., Python, C++, Go, Rust, or Java) and rapidly learning new development languages, software, frameworks, and APIs

Demonstrated knowledge of TCP, IPv4/6, Routing Protocols (one or more of BGP, MPLS, ISIS, or similar), and related network services (e.g., DHCP and DNS)

Experience developing and understanding network device configuration in multi-vendor environments (Juniper, Cisco, Arista, Brocade, etc.)

Experience in configuration and maintenance of network devices and NMS systems, or applications such as web servers, load balancers, relational databases, storage systems, and messaging systems

Hardware evaluation and vendor management experience

Preferred Qualifications

Proven experience designing, developing, and operating distributed systems at scale, with an in-depth understanding of the challenges and opportunities in this space

Experience designing and maintaining automated testing infrastructure to ensure the quality and reliability of network systems and tooling

Master's degree or graduate work experience in Computer Science, Computer Engineering, or a related technical field

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

In-depth knowledge of software and network debugging, profiling, and instrumentation techniques to ensure optimal system performance

Knowledge of IB/RDMA/RoCE Networks, including RDMA congestion control mechanisms, AI training workloads and demands they exert on networks

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

6+ years of experience building software solutions for managing network infrastructure, with a focus on scalability and reliability

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

About Meta

Meta concentrates its European engineering in Dublin, London and Paris, working on infrastructure, AI and core product. Headcount has been volatile since 2022, so treat the size of the board as a snapshot rather than a trend.

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