Principal AI Engineer – Computer Vision & Video AI

Al Khobar, Saudi Arabia

Up to SAR 50k per month

We're partnering with a technology company using AI to improve safety across large-scale industrial and construction environments. Their platform analyses live site video to identify potential hazards and provide teams with timely, actionable safety insights.

They're looking for a Principal AI Engineer to take technical ownership of the AI and perception stack. You'll stay hands-on while setting architecture, solving the hardest computer vision and applied AI problems, and influencing technical direction across the wider engineering team.

This is a genuinely deep technical role where video is at the centre of the product
, spanning computer vision, multimodal models, agentic AI, edge deployment and real-time systems.

• Own the technical direction of the computer vision and perception stack.
• Design and build production systems for object detection, segmentation, tracking and video understanding
  .
• Develop multimodal and vision-language systems that can reason over live and recorded video.
• Build AI agents capable of reasoning over visual data, using tools and APIs and operating within controlled workflows.
• Own the full model lifecycle from problem definition and data strategy through to experimentation, deployment, monitoring and continuous improvement.
• Optimise models across edge and cloud environments, balancing accuracy, latency, reliability and cost.
• Establish responsible AI and safety controls, including confidence thresholds, human review, explainability and auditability.
• Lead architecture reviews and document key technical decisions.

• Proven experience taking multiple production ML or computer vision systems from concept through to live operation
  .
• Deep hands-on experience working with video
  , including video streaming, analytics or computer vision over video.
• Strong experience with PyTorch or Tensor Flow across detection, segmentation, tracking and video understanding.
• Experience with both purpose-built computer vision models and transformer-based approaches.
• Production experience with vision-language or multimodal models
  , including model adaptation, prompting, evaluation and integration.
• Experience building agentic AI or tool-using systems
  , with appropriate guardrails and human-in-the-loop controls.
• Strong experience with dataset curation, fine-tuning, active learning and experiment management.
• Proven experience deploying AI workloads across edge and cloud infrastructure
  , with a focus on real-world latency, throughput and memory constraints.
• Strong MLOps and evaluation experience, including regression testing, experiment tracking, model versioning, monitoring and drift detection.
• Exceptional written and spoken English.

• RAG, vector search or multimodal retrieval experience.
• Real-time video or streaming camera systems.
• Edge AI technologies such as TensorRT, ONNX Runtime, Jetson or other GPU/NPU platforms.
• Self-hosted LLM/VLM serving using tools such as vLLM or similar.
• Experience in safety-critical, industrial or construction environments.
• Knowledge of EHS or workplace safety frameworks.
• Experience with privacy-focused video systems, including anonymisation, access controls and audit trails.