AI Engineer

Job Description

Looking for an AI engineer to develop, deploy, and operate AI/LLM models across clients' dual environment — GCP for public-cloud workloads, Humain sovereign cloud for classified data.

Requirements

Build and fine-tune LLM/ML models for Arabic NLP, document classification, vision/OCR, and AIOps use cases.

Run pre-deployment evaluation including accuracy baselines, regression, and safety testing; provide evidence to justify GPU allocation.

Optimize inference — quantization, batching, context sizing — against measured usage.

Deploy on Humain GPUaaS: Kubernetes, GPU partitioning on B300 nodes, quotas, RBAC.

Build equivalent workloads on GCP (Vertex AI, GKE) with classification-based routing.

Own serving stack (vLLM/TGI), model versioning, CI/CD, and monitoring for latency, tokens, GPU utilization, and drift.

Ensure developed AI models comply with ZATCA data sovereignty and SDAIA requirements (AI ethics, GenAI guidelines, PDPL).

Benefits

5 years of ML/AI engineering experience, including production LLM deployment.

Proficiency in Python, PyTorch, Hugging Face.

Kubernetes in production; GPU-served inference.

Experience with GCP Vertex AI or any equivalent cloud platform.