Principal AI Engineer

Principal Computer Vision & AI Engineer

Location: Al Khobar, Saudi Arabia

Role Overview

We are looking for a highly experienced Principal Computer Vision & AI Engineer to lead the technical direction of production AI systems operating over live video streams in real-world environments.

This is a hands-on technical leadership role rather than a people-management position. You will architect, build, optimise and deploy advanced computer vision, video understanding and multimodal/Vision-Language Model (VLM) systems while providing technical direction to senior engineers.

Key Responsibilities

• Architect and build production computer vision and video analytics systems.
• Develop solutions across object detection, segmentation, tracking, event understanding and spatial reasoning.
• Design and deploy VLM/multimodal AI systems operating over live and recorded video.
• Own the full ML lifecycle: data strategy, experimentation, fine-tuning, evaluation, deployment and monitoring.
• Optimise models for edge and cloud inference, balancing accuracy, latency, throughput and cost.
• Establish automated model evaluation, regression testing and production monitoring.
• Develop agentic AI systems capable of reasoning over video and interacting safely with tools, APIs, cameras and sensors.
• Set technical architecture and engineering standards while remaining highly hands-on with code.

What We're Looking For

• Deep hands-on experience in Computer Vision / Video AI.
• Strong production experience working with live or streaming video.
• Strong PyTorch and/or TensorFlow experience.
• Expertise across detection, segmentation and tracking using technologies such as YOLO, DETR/RT-DETR, GroundingDINO or equivalent.
• Production experience with Vision-Language Models / multimodal models such as Qwen-VL, InternVL, LLaVA, Gemini or equivalent.
• Experience deploying and optimising AI models in production.
• Exposure to edge AI, ideally TensorRT, ONNX Runtime, NVIDIA Jetson or similar.
• Strong understanding of model evaluation, MLOps, active learning and production monitoring.
• Ability to operate as a Principal/Staff-level technical authority while remaining hands-on.

Nice to Have

• Agentic AI / tool-calling systems such as LangGraph, LangChain or equivalent.
• Real-time CCTV, camera or video-streaming systems.
• Industrial, construction, robotics, autonomous systems or safety-critical AI experience.
• RAG / multimodal retrieval and vector search.
• Self-hosted VLM/LLM serving such as vLLM or NIM.

Critical requirement: Candidates must have substantial hands-on experience with video-based computer vision systems. Pure GenAI/LLM profiles without strong production video/CV experience will not be suitable.