AI Engineer

U X E SECURITY SOLUTIONS L.L.C; Dubai; On-site; AED 180,000 - 250,000; Full time

Job summary

UXE SECURITY SOLUTIONS L.L.C is seeking a production AI engineer to design, develop, and deploy computer vision and edge AI solutions. The role covers architecture, model development, optimization and integration across AI projects, collaborating with software, DevOps, and business teams from PoC to production.

The candidate will lead technical reviews, mentor engineers, and drive PoCs that advance UXE's AI capabilities, including Arabic/English RAG initiatives and robust monitoring.

Qualifications

• 4 years of professional experience in AI, ML or CV, including 2+ years in live production.
• Proven track record from PoC to deployment and ongoing operation.
• Experience with real-time image and video analytics at scale and tuning for accuracy/latency.
• Exposure to LLM, RAG or agentic AI development and technical leadership.
• Experience delivering technology projects in the UAE is strongly preferred.

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 performance.

Skills

Python

PyTorch

OpenCV

Linux

Docker

APIs

Production debugging

C++

CUDA

Kubernetes

Jetson

ONNX

TensorRT

Education

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, AI, ML, Computer Engineering or related field

Tools

NVIDIA Jetson

TensorRT

ONNX

CUDA

DeepStream

GStreamer

AWS/Azure/Google Cloud

Kubernetes

Job description

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. Hands-on role covering solution architecture, model development, optimization and integration across UXE's AI projects. Work with software, Dev Ops, infrastructure and business teams from PoC through deployment.

Job Responsibilities and Accountabilities

• 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, Tensor RT, CUDA, Deep Stream 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, Open CV, Linux, Git, Docker, APIs and production debugging, with disciplined code review and agile delivery practices.
• NVIDIA Jetson, ONNX, Tensor RT, and Deep Stream; 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.