System Architect – AI Networking

Location: Ra'anana

Hybrid

#IL-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 web architecture

The Role

As a System Architect – AI networking, you will define and evolve the system-level architecture for next-generation Network Operating Systems powering AI/ML infrastructure at scale. This role is centered on architecting software and control planes that are optimized for GPU-centric networking—including GPU <-> NIC <-> switch connectivity—and that meet the demands of ultra-low-latency, lossless, and high-throughput environments used in distributed training.

A key part of this role includes defining telemetry, orchestration, and automation capabilities that are AI workload-aware. You will design systems that observe and expose real-time metrics (e.g., congestion levels, link latency, queue depth, GPU-to-GPU path quality) and drive closed-loop optimization across the network. This includes defining how the NOS interacts with controllers, schedulers, and orchestration layers to adapt paths, resource allocation, and behavior dynamically.

This is a high-impact, cross-functional role that bridges deep technical expertise in networking systems, AI workload understanding, and system orchestration logic to deliver state-of-the-art connectivity platforms for AI-driven data centers.

Responsibilities

NOS Architecture for AI-Centric Fabrics

Define system-level architecture of the NOS to support AI training topologies and optimized GPU–NIC–switch interconnects.

Orchestration and Telemetry Frameworks

Architect telemetry infrastructure within the NOS for real-time monitoring of critical performance metrics: latency, congestion, buffer occupancy, packet drops, ECN marks, and GPU–GPU path health.
Define streaming telemetry pipelines, with export via OpenTelemetry, gNMI/gRPC, or custom APIs to orchestration/control platforms.

Requirements:

BSc/Msc in Computer Science / Electrical Engineering

4-5 years of experience in software development

2-3 years of experience in System Engineering / Architecture

Strong communication and collaboration skills. Ability to lead specifications from idea up to deployment

Strong analytical and problem-solving skills with a keen attention to detail.

Knowledge in networking and routing (L2/L3 protocols)

Knowledge in data path features such as QoS

Knowledge in management protocols and data modeling

If your experience is close but doesn’t fulfill all requirements, please apply. DriveNets is on a mission to build a special company comprised of individuals with different backgrounds, perspectives, and experiences.