Senior AI Solutions Engineer; AI Infrastructure, MLOps & Generative AI Platforms UAE

Job Title:

Senior AI Solutions Engineer (AI Infrastructure, MLOps & Generative AI Platforms) | Quantum Talent Group | Abu Dhabi, UAE

Recruiting Company:
Quantum Talent Group

Job Location:

Abu Dhabi, United Arab Emirates

Job Type: Full-Time

Send your CV to jean.fl

• Location:
  
  Abu Dhabi, UAE
• Customer-Facing Solution Design & Delivery Role
• Experience
  
  Required:
  
  8+ Years Infrastructure / Platform / Dev Ops Engineering
• AI/ML Experience
  
  Required:
  
  2+ Years
• Enterprise AI Platform Engineering Opportunity
• Immediate Hiring Requirement

Quantum Talent Group is seeking a highly experienced Senior AI Solutions Engineer to design, architect, and deliver enterprise-scale AI platforms supporting advanced AI, Machine Learning, and Generative AI workloads. This customer-facing role requires a strong blend of AI infrastructure expertise, cloud-native platform engineering, Kubernetes administration, GPU computing, and solution architecture capabilities.

As a Senior AI Solutions Engineer, you will lead the design and implementation of modern AI infrastructure platforms that enable enterprise AI, MLOps, Generative AI, and Agentic AI initiatives. You will work closely with customers, architects, data scientists, and engineering teams to design scalable solutions supporting Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and GPU-accelerated workloads. The role demands deep expertise in Kubernetes, Open Shift, NVIDIA GPU infrastructure, automation frameworks, and AI platform operations.

You will facilitate workshops, gather requirements, translate business challenges into technical architectures, and oversee end-to-end implementation delivery. This is an excellent opportunity to work at the forefront of enterprise AI transformation and next-generation intelligent computing platforms.

• Design and deliver enterprise AI infrastructure platforms supporting machine learning and Generative AI workloads.
• Architect scalable Kubernetes and Open Shift environments for AI, MLOps, and GPU-intensive applications.
• Design and implement NVIDIA GPU-enabled platforms for LLM training, inference, and AI workloads.
• Lead customer workshops, solution discovery sessions, and technical architecture discussions.
• Build and optimize infrastructure supporting Retrieval-Augmented Generation (RAG) and Agentic AI solutions.
• Implement infrastructure automation using Terraform, Ansible, Git Ops, and Infrastructure as Code practices.
• Develop Python-based automation scripts and platform management solutions.
• Design highly available, scalable, and secure AI platform architectures.
• Support GPU resource allocation, scheduling, sharing, and cluster optimization activities.
• Collaborate with AI engineers, data scientists, cloud architects, and Dev Ops teams.
• Provide technical leadership throughout solution delivery from design to production deployment.
• Ensure platform observability, operational readiness, security, governance, and performance optimization.

• Bachelor’s Degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
• Minimum 8 years of experience in Infrastructure Engineering, Platform Engineering, Dev Ops Engineering, or related disciplines.
• Minimum 2 years of hands‑on experience supporting AI/ML workloads or GPU‑accelerated computing environments.
• Strong production experience with Kubernetes and/or Open Shift deployments.
• Expertise managing Kubernetes/Open Shift on bare‑metal and virtualized infrastructure.
• Extensive experience with NVIDIA GPU infrastructure, CUDA, GPU scheduling, and GPU sharing technologies.
• Strong Infrastructure as Code (IaC) expertise using Terraform and Ansible.
• Experience implementing Git Ops methodologies and automation frameworks.
• Advanced Python scripting and automation experience.
• Hands‑on experience supporting Large Language Model (LLM) serving environments.
• Experience designing and supporting Retrieval-Augmented Generation (RAG) architectures.
• Strong solution architecture, stakeholder engagement, and customer workshop facilitation skills.
• Excellent troubleshooting, communication, and technical…