PURVIEW ASIA PACIFIC PTE. LTD. is hiring for a Network Automation and Reliability Engineer internship — a 12-month, hybrid Data Science role based in Singapore. It is an unpaid internship. It is open to university students, typically in Year 2–4. Applicants with experience in Microsoft Azure, systems reliability, AWS, Reliability Engineering Management, and Cross Functional Project Management are a strong fit.
⚡ New Data Science internships, the moment they're posted — join our Telegram
About this role
Roles & Responsibilities • Design, develop, and maintain network automation solutions using scripting and automation frameworks. • Automate network provisioning, configuration management, compliance checks, and change management processes. • Monitor network infrastructure performance, availability, and reliability across enterprise and cloud environments. • Develop and maintain observability, monitoring, and alerting systems for network services. • Troubleshoot and resolve network incidents, performance issues, and service disruptions. • Implement reliability engineering practices to improve network stability and minimize downtime. Skills/Requirements • Minimum of 8 years of progressive experience in network engineering, with at least 3 years focused on automation, reliability, and modernization initiatives. • Proven track record in designing and implementing enterprise-scale network automation frameworks using Ansible, Python, and CI/CD pipelines. • Deep expertise in core networking (routing, switching, firewalls, DNS, VPN, BGP, OSPF) and hybrid cloud networking (AWS, Azure). • Experience developing and managing AlgoSec or equivalent solutions for firewall automation. • Demonstrated success in leading cross-functional programs involving DevOps, Security, Cloud, and Application teams. • Strong background in observability, telemetry, and network performance monitoring. • Explore and evaluate emerging technologies such as intent-based networking, network digital twins, and AI-driven network analytics to drive continuous innovation.
Also in Data Science