AI Security - AI Platform Team Lead

Cato Networks is the converged network and security cloud for the AI era.

As AI reshapes cybersecurity, enterprises face a dual challenge: unlocking AI’s potential while defending against AI-driven attacks. Cato addresses both through a unified, cloud-native platform, providing the visibility and context to prioritize risks and stop threats in real time across users, applications, data, and AI agents.

Join us as we scale: take on ambitious technological challenges and shape the next generation of enterprise security at a company trusted by thousands of organizations worldwide.

Cato is building a real-time AI runtime platform for security algorithms running inline across our global cloud and physical PoPs.
We are looking for a hands-on AI Platform Team Lead to build and lead the team behind this platform: a high-throughput, low-latency engine that runs GPU-based models, from MMBERT-style models to LLMs, together with CPU-based heuristics and security logic.
This is a core infrastructure role for someone who wants to own the runtime layer of AI security at scale: performance, reliability, orchestration, GPU efficiency, and production-grade execution in the traffic path.
The team will also own the model lifecycle required to take AI security algorithms from research to large-scale production, working closely with research and algorithm teams.

Responsibilities

• Build and lead Cato’s AI Platform team: hiring, mentoring, architecture, technical direction, and execution.

• Own the AI security runtime platform for high-throughput, low-latency inline security decisions across Cato’s global cloud and PoPs.

• Design the orchestration layer for running GPU models, CPU heuristics, and security logic as one production engine.

• Own production readiness: observability, SLOs, autoscaling, reliability, rollout, rollback, and operational health.

• Own the model lifecycle platform: registry, versioning, deployment, monitoring, and safe production rollout.

• Work closely with research and algorithm teams to productionize AI security models and algorithms at scale.

• Define the long-term platform strategy for AI runtime and model serving at Cato.

Requirements

• 3+ years of leadership experience as a team lead, tech lead, or engineering manager.

• 3+ years of hands-on experience in AI inference, production ML infrastructure, model serving, or AI runtime platforms.

• Strong experience with production inference technologies such as Triton, vLLM, CUDA, Kubernetes, Docker, PyTorch, ONNX, TensorRT , or similar.

• 3+ years of experience with Go , or strong experience with a similar high-performance backend language such as C++, Rust, or Java.

• Experience with performance optimization, scalability, observability, and SLO-driven production ownership.

• Strong system design skills, especially around distributed systems, performance, reliability, and production infrastructure.

Advantages
Experience with GPU optimization, GPU scheduling, GPU resource efficiency, quantization, runtime acceleration, or large-scale model serving.