Lead Development & Sustenance Engineer

We are looking for an experienced Lead Development & Sustenance Engineer with strong expertise in SD-WAN Appliance, Data Plane, Control Plane, and Platform Sustenance .

🔹 Key Responsibilities

• Drive complex production/customer issues from triage through root-cause analysis, development, validation, and closure.
• Design, develop, debug, and sustain SD-WAN Data Plane, Control Plane, and platform components .
• Develop fixes and new features with strong focus on performance, scalability, reliability, and backward compatibility .
• Troubleshoot complex issues across packet processing, routing, sessions, policy, HA, configuration, and OS/hardware interactions .
• Improve product observability, diagnostics, logging, telemetry, and troubleshooting tools .
• Collaborate closely with Engineering, QA, Product, and Release teams to deliver high-quality releases.
• Contribute to regression prevention, release readiness, technical debt reduction, and product quality improvements.

🔹 Required Skills & Experience

• 10–20 years of software engineering experience in networking, distributed systems, or carrier/enterprise-grade products.
• Strong C/C++ programming and hands-on experience debugging multi-threaded, performance-sensitive systems .
• Deep understanding of IP networking – IPv4/IPv6, TCP/UDP, routing, OSPF, BGP, forwarding, tunneling, NAT, QoS, and packet flows .
• Mandatory: Hands-on experience with LACP, Link Aggregation, and interface management .
• Strong hands-on experience with SD-WAN / Router / Firewall / Networking appliances .
• Strong Linux systems knowledge and understanding of networking stack, IPC, system calls, memory, crash/core analysis, and performance debugging.
• Hands-on experience with GDB, packet capture tools, profilers, tracing, logs, telemetry, and automated testing .
• Experience handling production defects, intermittent issues, scale/performance issues, and release-branch fixes/backports .
• Mandatory: Experience with issue triaging using SlashTriage and AI-augmented engineering tools .
• Strong ownership, analytical/problem-solving skills, and excellent communication.

Education: Bachelor's or Master's degree in Computer Science, Electrical Engineering, Information Systems, or a related field.