Datapath Software Engineer - AI Datacenter Networking

DESCRIPTION

Location: Tel Aviv

#Hybrid

DriveNets is a leader in high-scale disaggregated networking solutions. Founded in 2015, DriveNets modernizes the way service providers, cloud providers and hyperscalers build networks. Supporting the largest network in the world, more than half of AT&T’s backbone traffic is running on DriveNets’ Network Cloud open disaggregated architecture. Raising $587 million in three funding rounds, DriveNets is disrupting the networking market from high-scale architecture to AI platforms, and is bringing onboard the most talented people. We are seeking people that want to make an impact on the world’s leading communication networks and are experienced in networking architecture or AI infrastructure solutions.

Job Summary:

Develop and optimize high-performance datapath software for AI datacenter networking, implementing SONiC enhancements, smart NIC integration, and specialized routing features for AI workloads.

Key Responsibilities:

Implement datapath features in SONiC for AI-optimized networking scenarios
Develop smart NIC integration drivers and control plane software
Optimize packet processing performance for AI training and inference traffic
Implement RDMA and high-speed networking protocol support
Create monitoring and telemetry collection mechanisms for datapath analysis
Implement load balancing algorithms optimized for AI workload patterns
Debug and optimize datapath performance bottlenecks
Collaborate with QA teams on feature testing and validation
Contribute to open-source SONiC community and maintain vendor-specific extensions

REQUIREMENTS

Required Qualifications:

BSc degree in Computer Science or Engineering
5+ years of software development experience in networking or systems programming
Strong proficiency in C/C++ and Python programming
Understanding of networking protocols and packet processing optimization
Strong debugging skills with networking and performance analysis tools

Preferred Qualifications:

Experience with SONiC development, SAI implementation, or switch software
Knowledge of Linux kernel networking
Experience with smart NIC programming interfaces and SDK development
Familiarity with DPDK, RDMA, and high-performance networking libraries
Experience with AI/ML framework networking integration