Summary
The role designs, develops and deploys production AI solutions for UXE, concentrating on computer vision, video analytics and edge AI, while also supporting Arabic/English agentic AI initiatives.
Job Description
Hands-on role covering solution architecture, model development, optimization and integration across UXE's AI projects. Work with software, DevOps, infrastructure and business teams from PoC through deployment.
Responsibilities
• Design and evaluate detection, tracking, segmentation, classification and video-analytics solutions.
• Build low-latency multi-camera pipelines for NVIDIA Jetson and GPU platforms.
• Optimize models using ONNX, TensorRT, CUDA, DeepStream or GStreamer and measure accuracy, precision and recall, false alarms, throughput and latency.
• Integrate AI with APIs, databases, VMS, cameras and backend systems; implement monitoring, resilience and rollback so deployed systems are robust, scalable and maintainable.
• Develop and evaluate Arabic/English RAG, LLM and agentic workflows with guardrails and human review.
• Work with cross-functional teams to capture project requirements and deliver AI solutions that meet business needs.
• Lead technical design, code/model reviews, documentation, mentoring, customer workshops and production troubleshooting.
• Track advances in AI, machine learning and computer vision; conduct research and internal PoCs that contribute to the continuous improvement of UXE's AI capabilities.
Experience Required
• 4 years of professional experience in AI, machine learning or computer vision, including at least 2 years delivering systems into live production.
• Proven track record of taking AI solutions from proof of concept through deployment and ongoing operation.
• Experience with real-time image and video analytics at scale, including tuning against accuracy, latency and throughput targets.
• Exposure to LLM, RAG or agentic AI development, together with technical leadership or mentoring of engineers.
• Experience delivering technology projects in the UAE is strongly preferred.
Qualifications
• Bachelor’s or Master’s degree in Computer Science ,Electrical Engineering, AI, Machine Learning, Computer Engineering or a related field.
• Equivalent practical experience may be considered with a strong portfolio of deployed AI systems.
• A Ph.D. in a relevant field is an advantage
Technical Skills Required
• Python, PyTorch, OpenCV, Linux, Git, Docker, APIs and production debugging, with disciplined code review and agile delivery practices.
• NVIDIA Jetson, ONNX, TensorRT, and DeepStream; CUDA and C++ are advantageous.
• Cloud platforms (AWS, Google Cloud or Azure) and container orchestration with Kubernetes are advantageous for hybrid edge-cloud deployments.
• LLM/RAG/agent frameworks, vector databases, evaluation and guardrails; Arabic AI experience is preferred.
Soft Skills
• Strong ownership, analytical troubleshooting, creative problem-solving and sound technical judgement.
• Clear communication of technical concepts to both technical and non-technical stakeholders, with strong documentation, teamwork and mentoring ability.
• Able to balance model quality, performance, hardware constraints and operational risk.
