Senior RDMA Performance Engineer

CodiLime is a software and network engineering industry expert and the first-choice service partner for top global networking hardware providers, software providers and telecoms. The company has over 250 employees and has been operating since 2011. Their clients include tech startups and major companies in US, Japan, Israel, and Europe. CodiLime creates proofs-of-concept, helps clients build new products, nurtures existing products, and provides production services.

• 7+ years of professional experience in network engineering, with preferably 3+ years focused on data center network design and architecture.
• Hands-on experience configuring and troubleshooting core protocols and technologies including BGP, EVPN/VXLAN, LACP, and ECMP.
• Deep understanding and practical experience with AI-dedicated data center designs such as Rail-Optimized Design (ROD) and Rail-Unified Design (RUD).
• Proven experience configuring, managing, and troubleshooting NVIDIA/Mellanox Spectrum switches and ConnectX NICs.
• Deep understanding of protocols and congestion control mechanisms for AI data centers, specifically RoCEv2, Priority-based Flow Control (PFC), and Explicit Congestion Notification (ECN).
• Ability to tune and optimize network environments with focus on switch buffer tuning and Quality of Service (QoS) policy implementation.
• Experience in performance benchmarking and validation for AI-ready data center fabrics using RDMA and NCCL.
• Ability to leverage AI agents/tools to automate testing and analysis.
• Strong technical documentation skills and professional English communication.

Nice to have:

• Professional certifications such as CCNP, CCIE Enterprise/DC, or JNCIP.
• Experience with network automation and validation frameworks: pyATS, NAPALM, Batfish, Nornir, NetBox.
• Exposure to CI/CD pipelines (GitLab CI, GitHub Actions, Jenkins) and Infrastructure as Code (IaC) concepts.

• Configure, troubleshoot, and maintain NVIDIA/Mellanox Spectrum switches and ConnectX Network Interface Cards (NICs).
• Implement and tune advanced congestion control mechanisms essential for AI workloads, including RoCEv2, Priority-based Flow Control (PFC), and Explicit Congestion Notification (ECN).
• Optimize network environments to ensure maximum throughput, minimal latency, and minimal Job Completion Time (JCT) by performing setup tuning.
• Conduct extensive performance benchmarking and validation testing on AI-ready data center fabrics utilizing RDMA and the NVIDIA Collective Communication Library (NCCL).
• Leverage AI agents and specialized tools to automate routine network tasks, conduct rigorous testing, and analyze network telemetry.
• Author and maintain clear, high-quality technical documentation detailing network designs, configurations, and benchmarking results.