
Production Engineer, Network AI Lead
Required skills
- Network AI
- Production Engineer
- Network Infrastructure
- backbone
- datacenter
- AI network
- data center network
- automation
- release engineering
- configuration management
Nice to have
- physical network infrastructure
- rack solutions
- fiber connectivity
- automated design synthesis
- AI cluster fabrics
- GPU cluster fabrics
Role summary
Meta's Network Infrastructure team seeks a Production Engineer, Network AI Lead to design, build, and operate a large-scale global network, focusing on backbone, datacenter, and AI network domains. This hybrid role involves creating innovative, scalable network solutions, developing automation and tools for deployment and operations, and investigating complex technical issues. The engineer will influence future networking infrastructure, enhance operational efficiency through automation, and contribute to team growth. The role requires a Bachelor's degree in a technical field or equivalent experience, 8+ years of relevant experience, proficiency in higher-level programming languages like Python or C++, and experience with network devices and systems. Preferred qualifications include expertise in physical network infrastructure design, AI integration, and advanced routing topologies.
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 their goals
- Participate in an oncall 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
- Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
- 8+ years of relevant experience in developing scalable and reliable systems and/or networks
- Experience coding in higher-level languages (e.g., Python, C++, Go, Rust, etc.)
- Experience learning software, frameworks, and APIs
- Experience in the configuration and maintenance of network devices and NMS systems, or applications such as web servers, load balancers, relational databases, storage systems, and messaging systems
- Experience developing and understanding network device configuration for at least one vendor (Juniper, Cisco, Arista, Brocade, etc.)
Preferred Qualifications
- Experience with physical network infrastructure design including rack solutions, fiber connectivity, and automated design synthesis for AI or GPU cluster fabrics, ring interconnects, or backbone aggregation topologies
- 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)
- Experience with centralized or hybrid routing design, including synthesis and verification frameworks for large-scale multiplanar or disaggregated network topologies
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience integrating AI-assisted workflows or automation tooling to accelerate network design, testing, or operational processes with measurable efficiency or quality improvements
- Experience qualifying new network hardware platforms and optics through structured NPI frameworks, including end-to-end validation and targeted feature qualification
$184,000/year to $257,000/year + bonus + equity + benefits
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