Production Network Engineer

Socket.dev; Menlo Park (CA); On-site; USD 135,000 - 191,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Socket.dev in Menlo Park, CA is seeking a senior network engineer to lead the design and delivery of large-scale production network projects across data center fabrics, backbone infrastructure, and edge services.

You will drive technical strategy for reliability, capacity, and operational efficiency, and develop automation to reduce manual work while accelerating design, build, and configuration management. The role requires strong routing expertise and leadership with AI tooling awareness.

Qualifications

• Bachelor's degree or equivalent practical experience in Computer Science, Engineering, or related field.
• 6+ years of production network engineering experience including design, deployment, and operations of large-scale data center or backbone networks.
• Experience with routing protocols (BGP, OSPF, IS-IS) and MPLS in production environments.
• Experience developing and deploying network automation using Python or similar languages.
• Experience leading cross-functional network reliability or infrastructure projects, including incident response and root-cause analysis.
• Experience influencing technical decisions and network strategy across engineering teams.

Responsibilities

• Lead the design and delivery of large-scale production network projects across data center fabrics, backbone infrastructure, and edge services.
• Define and drive technical strategy and roadmap for reliability, capacity, and efficiency across multiple teams.
• Develop automation frameworks to reduce manual overhead and accelerate design, build, and config management.
• Own cross-functional incident response and post-incident reviews to drive systemic improvements.
• Identify and resolve complex network performance, routing, and reliability issues across multi-vendor environments.
• Collaborate with architecture, capacity planning, and software teams to align infra with AI/product demand forecasts.
• Refine runbooks and monitoring to improve observability and mean time to detection/resolution.
• Contribute to team goals by defining scalable network operations approaches and tooling decisions across engineering teams.
• Advise engineers on best practices, operational discipline, and systems thinking.
• Leverage AI-integrated workflows to accelerate analysis, anomaly detection, and documentation.

Skills

Network engineering

Cross-functional leadership

Incident response

Network automation

Stakeholder alignment

AI tooling awareness

Education

Bachelor's degree

Tools

BGP

OSPF

IS-IS

MPLS

Python scripting

Job description

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 technical strategy and roadmap contributions 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, build processes, 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 team-level goals by defining scalable approaches to network operations and influencing tooling and platform decisions across engineering teams
• Advise 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

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 6+ years of experience in production network engineering, including design, deployment, and operations of large-scale data center or backbone network infrastructure
• Experience with routing protocols and network technologies including BGP, OSPF, IS-IS, MPLS, and large-scale Ethernet fabrics in a production environment
• Experience developing and deploying network automation using scripting or programming languages such as Python to manage configuration, provisioning, or monitoring at scale
• Experience leading cross-functional network reliability or infrastructure projects, including driving incident response, root cause analysis, and systemic remediation
• Experience influencing technical decisions and network strategy across engineering teams through written proposals, design reviews, and stakeholder alignment

Preferred Qualifications

• Experience operating and troubleshooting networks at hyperscale, including multi-vendor spine-leaf data center fabrics and global backbone interconnects
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Familiarity with software-defined networking principles, network operating system internals, or co-development of network management platforms with software engineering teams
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience with network observability platforms, traffic engineering, and capacity modeling in high-throughput production environments
• Experience integrating AI tools to redesign network operations workflows and deliver measurable improvements in efficiency or reliability outcomes

$135,000/year to $191,000/year + bonus + equity + benefits