Network Engineer III (Automation & AIOps)

Job Summary 

Responsible for network design, planning, and operations, including capacity management, vendor evaluation, project management, and service lifecycle management, with automation and AI-driven tooling built into how the work gets done rather than layered on top of it. Applies coding, scripting, and AI-driven insights to improve network efficiency, reliability, and scalability, and to reduce manual operational overhead. Requires strong understanding of network architecture principles and modern infrastructure (data center, cloud, interconnection), along with working fluency in automation and AIOps practices. 

Responsibilities :

Deployment 

• Deploys new hardware (Multi-vendor) in accordance with documented guidelines 

• Manage deployment project life cycle end to end. 

• Partners with hardware validation teams on qualification of new equipment 

• Support the Network platform operations and participate in standby. 

• Participates in port, device, and customer migrations, as needed. 

• Performs deployments of network tools and new features, and owns new feature enablement 

• Builds and applies automation (Python, scripting) to streamline and standardize deployment processes, reducing manual touchpoints 

Product Development Lifecycle 

• Provides feedback as the voice of the customer based on customer queries and trouble tickets 

• Leverages data analytics and AI tools to surface recurring issues and improvement areas from ticket and query trends 

• Builds and applies automated test frameworks and validation scripts to reduce manual test cycles. 

• Manages and sustains deployments post-transition to achieve high customer satisfaction 

• Uses AI-assisted monitoring and predictive analytics to catch degradation before it becomes customer-impacting 

Service Delivery 

• Performs network service fulfillment (quote-to-cash) for network and data center products. 

• Ensures successful fulfillment of software-triggered provisioning for interconnection services. 

• Reviews fulfillment of metrics and identifies opportunities for automation-driven efficiency gains. 

• Builds and implements automation and data-driven optimization for fulfillment processes. 

Operations and Reliability Engineering 

• Troubleshoots and resolves network faults, both reactive and through proactive detection 

• Performs preventive maintenance to minimize incidents 

• Utilizes AI-based monitoring tools including anomaly detection and predictive alerting 

• Develops automation scripts and tooling to accelerate root cause analysis and reduce mean-time-to-resolution (MTTR) 

Innovation 

• Participates in internal innovation programs and hackathons 

• Uses lab environments for technical practice and validation 

• Participates in chaos engineering drills to test operational resilience 

• Develops automation tools (Python, APIs) for chaos testing and resilience engineering 

• Explores AI/ML use cases for network optimization and incident prediction 

• Utilizes AI tools to optimised the deployment process lifecycle. 

Technical Skills:

Programming and Automation 

• Python and scripting (required) 

• API integration for network automation, including REST (required) 

• Infrastructure as Code (nice to have) 

AI and Data 

• Working understanding of AI/ML concepts as applied to network operations, or AIOps (required) 

• Experience with data analysis, log analysis, and anomaly detection (required) 

• Familiarity with AI-driven monitoring tools (preferred) 

Network Architecture 

• Strong understanding of IP networking, including L2/L3, BGP, and routing 

• Strong understanding of data center architecture and interconnection services 

• Strong understanding of scalability and redundancy design 

• Knowledge of modern network architecture including cloud, hybrid, and SDN 

Qualifications :

• 5+ years of experience in Network Operations or Network Engineering 

• Bachelor’s degree or equivalent practical experience 

• Strong understanding of network architecture and operations 

• Demonstrated experience in coding and automation applied to real operational tooling, Python preferred 

• Experience in AI-driven operations (AIOps) required