À propos de ce poste Senior Platform Software Engineer – IPsec/VPP/Kubernetes chez Parallelwireless
We are looking for a highly experienced Senior Network Platform Software Engineer with 8–12 years of hands-on software/platform development experience in networking, telecom, or high-performance networking domains.
The role will primarily focus on network platform development, feature implementation, code-level debugging, issue resolution, and system integration across IPsec, VPP, StrongSwan, Linux networking, Docker, and Kubernetes. The engineer will also contribute to AI-assisted engineering initiatives, developing tools to automate log analysis and improve root-cause identification and debugging efficiency.
What you'll do:
Develop and enhance networking features involving IPsec/IKE, routing, traffic selectors, SPD/SAD, tunnels, and traffic segregation.
Work with existing codebases to understand implementation flows, modify code, implement fixes, and resolve defects.
Debug complex networking scenarios across multi-tunnel, multi-network, VLAN, container, and Kubernetes environments.
Perform end-to-end troubleshooting and RCA across application, container, networking, VPP/DPDK, and Linux kernel layers.
Develop and enhance AI-assisted tools for automated log analysis and root-cause identification, and collaborate across teams to drive complex issues through resolution.
What you should have:
Strong hands-on experience with IPsec, VPP, and StrongSwan, including implementation, debugging, and integration.
Strong Linux/Kernel networking expertise, including packet flow, CPU/IRQ, performance, and system-level debugging.
Hands-on experience with Docker/Kubernetes networking, including CNI/Multus, SR-IOV, pod/service networking, and cluster debugging.
Experience with VPP/DPDK and high-performance networking is highly desirable.
Strong C/C++ programming and debugging skills, with Python/scripting skills for automation, analysis, and development of engineering tools.
AI & Automation – Good to Have:
Interest or experience in applying AI to software development, log analysis, debugging, and RCA automation.
Experience with automation, log-processing, or internal debugging/analysis tools.
Nice to Have:
Experience with Linux kernel networking internals and system debugging tools.
Experience with SR-IOV, Multus, CNI, and cloud-native telecom networking.
Experience with high-performance packet processing and telecom networking products.
Role Evolution:
The initial focus will be on understanding the existing networking implementation, codebase, architecture, and failure patterns. Over time, the engineer will take increasing ownership of feature development, code-level debugging, defect resolution, performance optimization, and AI-assisted RCA capabilities.
The objective is to build strong engineering ownership across the networking stack, from application and container layers through IPsec, VPP/DPDK, Linux networking, and kernel layers, while using AI-assisted automation to improve log analysis, debugging efficiency, and root-cause accuracy.
