AI Engineer

Looking for an AI Engineer to Develop, deploy, and operate AI/LLM models across Clinets dual environment — GCP for public-cloud workloads, Humain sovereign cloud for classified data. Benefits 5 years ML/AI engineering, in production LLM deployment with knowledge in Python, PyTorch, Hugging Face Kubernetes in production; GPU-served inference GCP Vertex AI or any equivellent cloud

Develop, deploy, and operate AI/LLM models across dual environments (GCP and Humain sovereign cloud). Manage end-to-end model lifecycle including serving stack ownership, versioning, CI/CD, monitoring for latency, token throughput, GPU utilization, and drift. Implement pre-deployment evaluation, safety checks, and accuracy baselines. Optimize inference performance (quantization, batching, context sizing) and manage resource allocation (GPU quotas, partitioning, RBAC). Implement and maintain routing between GCP Vertex AI/GKE and Humain Kubernetes deployments. Ensure compliance with data sovereignty and regulatory guidelines (ZATCA, SDAIA, PDPL) and adhere to AI ethics and GenAI guidelines.