AI Security - AI Platform Engineer - Cato Networks

3+ years of hands-on experience in AI inference, production ML infrastructure, model serving, or MLOps. Experience with production inference technologies such as Triton, vLLM, CUDA, Kubernetes, Docker, PyTorch, ONNX, TensorRT , or similar. Strong understanding of low-latency, high-throughput production systems. Experience with model lifecycle concepts: model registry, versioning, deployment, rollout, rollback, monitoring, and observability. 3+ years of experience with Go , or strong experience with a similar high-performance backend language such as C++, Rust, or Java.

Build Cato’s AI security runtime platform for high-throughput, low-latency production serving. Develop infrastructure for model serving, multi-model orchestration, and inline decision flows. Optimize inference performance: batching, caching, streaming, GPU utilization, memory usage, and runtime acceleration. Build backend orchestration and performance-critical services in Go. Support the model lifecycle: registry integration, packaging, versioning, deployment, monitoring, and operational health. Work closely with research and algorithm teams to productionize AI security models and algorithms at scale.

3+ years of hands-on experience in AI inference, production ML infrastructure, model serving, or MLOps. Experience with production inference technologies such as Triton, vLLM, CUDA, Kubernetes, Docker, PyTorch, ONNX, TensorRT , or similar. Strong understanding of low-latency, high-throughput production systems. Experience with model lifecycle concepts: model registry, versioning, deployment, rollout, rollback, monitoring, and observability. 3+ years of experience with Go , or strong experience with a similar high-performance backend language such as C++, Rust, or Java.