Senior Platform Software Engineer – IPsec/VPP/Kubernetes

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.

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.

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.

Design, develop, debug, integrate, and maintain networking/platform software involving IPsec, VPP, StrongSwan, and Linux networking.

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:

8–13 years of hands-on software/platform development experience, preferably in networking or telecom.

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.

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:

Exposure to AI/LLM-based developer tools or coding assistants.

Interest or experience in applying AI to software development, log analysis, debugging, and RCA automation.

with automation, log-processing, or internal debugging/analysis tools.

Nice to Have:

Experience with VPP/DPDK datapath development and performance optimization.

with Linux kernel networking internals and system debugging tools.

with SR-IOV, Multus, CNI, and cloud-native telecom networking.

with high-performance packet processing and telecom networking products.

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.