Network Engineer III

About the role

Equinix, a digital infrastructure company, is looking for a Network Engineer III responsible for network design, planning and operations, including capacity management, vendor evaluation, project management and service lifecycle management. The role also uses AI-driven insights, automation and coding to improve network efficiency, reliability and scalability, and requires a strong understanding of network architecture and modern infrastructure such as data centers, cloud and interconnection.

Key responsibilities

• Deploy single-vendor hardware according to documented guidelines, validate it with GNA, train NOC staff, perform RMA actions and take part in port, device and customer migrations
• Apply Python and scripting automation to streamline deployments and enable new features
• Act as the customer's voice during the requirement phase, using data analytics and AI tools to spot recurring issues; take part in SIT and UAT, run automated tests and transition deployments to sustaining teams
• Deliver network and datacenter services (quote-to-cash), ensure software-triggered provisioning works, review metrics and automate fulfillment processes
• Troubleshoot network faults proactively and reactively, run preventive maintenance, use AI-based monitoring and build scripts for faster root cause analysis
• Take part in Sparkathons, chaos engineering drills and innovation activities, and explore AI/ML use cases for network optimization

Required profile

• 5+ years of experience in network operations or engineering
• Bachelor's degree or equivalent experience
• Strong understanding of network architecture and operations
• Experience in coding and automation (Python preferred); interest in AI-driven operations (AIOps) is a plus

Required skills

• Python and scripting (required)
• API integration (REST, network automation)
• IP networking (L2/L3, BGP, routing), data center architecture, interconnection services, cloud, hybrid and SDN architectures
• Data analysis, log analysis and anomaly detection; basic understanding of AI/ML concepts; familiarity with AI-driven monitoring tools preferred
• Infrastructure as Code (nice to have)