Global Network Production & Automation Engineer

Menlo Park (CA)

Hybrid

USD 210,000 - 320,000

Full time

6 days ago

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Job summary

Meta is seeking a Production Network Engineer to join the Network Infrastructure team in Menlo Park. You will design, build, and operate our global backbone, datacenter, and AI network deployments at scale.

As a hybrid software and network engineer, you will develop automation tools, drive CI/CD for network software, mentor peers, and collaborate with hardware, software, and sourcing teams to improve reliability and efficiency across the worldwide network.

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 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)
Knowledge of IB/RDMA/RoCE Networks, including RDMA congestion control mechanisms, AI training workloads and demands they exert on networks
Proven experience designing, developing, and operating distributed systems at scale, with an in-depth understanding of the challenges and opportunities in this space
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)
In-depth knowledge of software and network debugging, profiling, and instrumentation techniques to ensure optimal system performance
Experience designing and maintaining automated testing infrastructure to ensure the quality and reliability of our systems
Master's degree or graduate work experience in Computer Science, Computer Engineering, or a related technical field

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 find gaps that impact multiple teams, come up with the execution plan, drive the project, and influence other teams to reach there
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