We’re an award-winning global communications company operating in nine countries across the Middle East, North Africa, and Southeast Asia. Our strategy is to become the region’s leading digital infrastructure provider. Ooredoo Group’s strategic vision is guided by five key pillars:
Value-Focused Portfolio: Boosting asset returns by focusing on telco operations, towers, data centres, the sea cable business and fintech.
Strengthen the Core: Optimally using deployed capital and maintain an appropriate cost structure.
Evolve the Core: Monetising opportunities to generate new revenue streams via programmes focusing on analytics, digitalisation of operations, and partnerships with digital service providers.
People: Building an engaged and empowered workforce through integrated learning programs and coaching and mentoring.
Excellence in Customer Experience: Creating superior customer experiences.
From day one, every employee who joins our team becomes an integral part of our success journey. We offer you the chance to enhance your skills, advance your career, and maintain a healthy work-life balance. Empowering you to catapult your personal and professional growth. If you’re looking to challenge your growth potential, Ooredoo is the employer for you.
The AI Solution Architect Lead will design scalable and high-performance AI solutions that align with the strategic objectives of the organization. This role is responsible for translating business requirements into technical architectures, ensuring that AI models and systems integrate seamlessly with existing technologies across OpCos. The Solution Architect will work closely with the AI Engineers, Data Scientists, and Business Analysts to create sustainable, adaptable, and efficient AI systems that drive business value.
Architectural Design: Develop and maintain the overall AI architecture, ensuring it is scalable, secure, and aligned with the organization’s business goals. Provide architectural blueprints and technical leadership to AI teams across HQ and OpCos.
Solution Development: Design end-to-end AI solutions that integrate data processing, machine learning, and AI models into the existing business infrastructure, ensuring alignment with both technical and business requirements.
Technology Evaluation: Stay up to date with emerging AI technologies and tools. Evaluate and recommend new tools and platforms that can enhance AI performance and scalability within the organization.
Collaboration: Work closely with AI Engineers, Data Scientists, and Business Analysts to ensure that AI models are well-integrated into the business process and technical ecosystem, considering both local (OpCo) and global (HQ) needs.
Technical Leadership: Provide technical guidance and mentorship to AI Engineers and Data Engineers. Ensure best practices for AI model design, deployment, and scalability are followed.
System Integration: Ensure seamless integration of AI systems with other enterprise systems (e.g., CRM, ERP, marketing platforms). Oversee technical execution to ensure that the system design and AI solutions are properly implemented.
Security and Compliance: Ensure that AI solutions meet the organization’s security and compliance requirements, including data governance, privacy regulations, and ethical AI guidelines.
Performance Optimization: Continuously monitor the performance of AI systems and identify opportunities to optimize architecture and model efficiency.
7+ years of experience in solution architecture or related roles, including 3+ years of experience in AI or data-intensive projects.
Proven experience designing and implementing scalable AI or machine learning architectures.
Strong understanding of cloud-based AI solutions (e.g., AWS, Google Cloud, Azure) and AI-related tools (e.g., TensorFlow, PyTorch).
Experience in systems integration and working with large-scale enterprise infrastructure.
Experience in telecommunications or a related industry.
Bachelor’s degree in computer science, Engineering, or related field (Master’s degree preferred).
Experience with MLOps and AI lifecycle management tools.
Strong knowledge of cloud infrastructure and AI service providers.
Experience with AI system performance optimization techniques.