Lead AI Architect

Role Overview

Company Context

Architecture Responsibilities

• Architect enterprise GenAI, LLM, RAG, and AI/ML platforms for secure on-premise and air-gapped environments.
• Design GPU-accelerated infrastructure using NVIDIA DGX, H100/B200, NVLink, and NVSwitch.
• Architect AI platforms on Red Hat OpenShift and Kubernetes using the NVIDIA GPU Operator.
• Design and integrate NVIDIA NIM, Triton Inference Server, DataRobot, and graph databases.
• Build architectures supporting RAG, Knowledge Graphs, and enterprise data pipelines.
• Define security, scalability, performance, and data-sovereignty standards for banking environments.

Leadership Responsibilities

• Provide technical leadership and guidance to Data Science, Engineering, and AI teams.
• Evaluate emerging AI technologies and drive adoption of solutions that create measurable business impact.
• Translate business requirements into scalable AI solutions with cross-functional and client teams.

Required Experience

• Candidates need 8+ years of experience in AI/ML, enterprise architecture, infrastructure, or related areas.
• Candidates need 3+ years designing large-scale GenAI, LLM, AI/ML, or GPU-accelerated solutions.
• Strong experience with NVIDIA GPUs, OpenShift, Kubernetes, and GPU Operator is required.
• Hands-on knowledge of NVIDIA NIM, Triton Inference Server, DataRobot, and graph databases is required.
• Strong understanding of RAG, LLM infrastructure, distributed systems, and AI platforms is required.
• Experience in Banking, BFSI, FinTech, or highly regulated environments is required.
• Strong stakeholder management, problem-solving, and technical leadership skills are required.

Preferred Experience

• Experience with air-gapped environments, large-scale LLM inference, Knowledge Graphs, Agentic AI, or recommendation systems is advantageous.

Workplace and Industry

• The position is on-site in Saudi Arabia.
• The primary industry context is banking and financial services.