AI Engineer

Develop, deploy, and operate AI/LLM models across Clinets dual environment—GCP for public-cloud workloads and Humain sovereign cloud for classified data. Build and fine-tune LLM/ML models for Arabic NLP, document classification, vision/OCR, and AIOps use cases, running pre-deployment evaluation including accuracy baselines, regression, and safety testing to justify GPU allocation. Optimize inference through quantization, batching, and context sizing, then deploy on Humain GPUaaS using Kubernetes, GPU partitioning on B300 nodes, and quotas. Manage equivalent workloads on GCP with classification-based routing, owning the serving stack, model versioning, and monitoring for latency, tokens, and drift while ensuring compliance with ZATCA data sovereignty and SDAIA requirements. Requires five years of ML/AI engineering experience in production LLM deployment.