Job Description

Roles & Responsibilities

The Senior AI Solution Architect will translate complex business, operational, and transportation requirements into secure and scalable AI architectures. The position combines enterprise solution design with practical knowledge of Generative AI, Large Language Models, analytics platforms, cloud environments, APIs, data systems, and production AI operations. Working across technology, data, cybersecurity, analytics, and operational teams, the specialist will shape how AI capabilities move from initial concepts and proofs of value into dependable production solutions. The role will also influence technology selection, architecture standards, model lifecycle practices, integration patterns, and technical governance across digital transformation initiatives.

Key Responsibilities

• Lead architecture design for AI-enabled transportation, mobility, infrastructure, and digital transformation solutions.
• Define end-to-end technical architectures covering AI platforms, enterprise applications, APIs, data pipelines, integration services, cloud environments, and operational systems.
• Assess existing client technology landscapes to identify realistic opportunities for Artificial Intelligence, Generative AI, machine learning, advanced analytics, and intelligent automation.
• Evaluate proposed AI use cases for technical feasibility, scalability, system dependencies, operational impact, and implementation complexity.
• Establish architecture principles, technology standards, integration patterns, and technical requirements for AI solutions.
• Develop conceptual and logical architecture diagrams, solution designs, deployment approaches, and implementation roadmaps.
• Coordinate with data engineering, analytics, cybersecurity, cloud, enterprise architecture, and application teams to build secure and maintainable solutions.
• Evaluate AI platforms, frameworks, development tools, technology vendors, and implementation partners against project requirements.
• Provide technical oversight throughout AI solution development, integration, testing, deployment, and operational readiness.
• Define approaches for model deployment, monitoring, performance measurement, version management, and ongoing lifecycle governance.
• Support proof-of-concept projects and pilot deployments before transitioning validated capabilities into production environments.
• Review technical deliverables and architecture designs to confirm quality, scalability, security, and alignment with agreed standards.
• Guide the integration of AI services with enterprise applications, operational technology, geospatial platforms, mobility systems, and digital business solutions.
• Contribute to architecture decisions involving LLMs, Retrieval-Augmented Generation, AI agents, vector databases, intelligent search, and knowledge management platforms.
• Support the development of responsible AI controls addressing governance, privacy, cybersecurity, regulatory requirements, and operational risk.

Ideal Profile

Candidates should hold a technical degree from an accredited university in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a closely related discipline. A minimum of 10 years of professional experience is required across solution architecture, AI implementation, analytics platforms, enterprise technology, or digital solution delivery. The strongest profiles will demonstrate hands-on architectural experience with:

• Artificial Intelligence and machine learning solutions
• Generative AI applications
• Large Language Models
• Retrieval-Augmented Generation
• AI agents and orchestration
• Advanced analytics platforms
• Enterprise application integration
• Cloud and data platforms
• AI deployment and operationalisation
• Model monitoring and lifecycle governance

Candidates should understand MLOps, LLMOps, CI-CD pipelines, automated testing, model versioning, production deployment, and performance management practices. Previous work involving transportation, intelligent transportation systems, mobility platforms, smart cities, digital infrastructure, or large technology transformation programmes would be particularly relevant. Experience with digital twins, predictive analytics, operational intelligence, or decision-support systems is advantageous. Professional certifications covering AI, cloud computing, enterprise architecture, or related technology disciplines are beneficial. Middle East experience and Arabic language capability are additional advantages.

Skills Set

• AI solution architecture
• Artificial Intelligence
• Generative AI
• Large Language Models
• Retrieval-Augmented Generation
• RAG architecture
• AI agents
• Machine learning
• Advanced analytics
• Intelligent automation
• Enterprise architecture
• Solution design
• Cloud architecture
• Data platforms
• API integration
• Application integration
• Vector databases
• AI orchestration frameworks
• Knowledge management platforms
• Intelligent search
• MLOps
• LLMOps
• CI-CD pipelines
• Model deployment
• Model versioning
• AI performance monitoring
• Model lifecycle management
• Proof-of-concept development
• AI production deployment
• Responsible AI
• AI governance
• Cybersecurity
• Data privacy
• Digital twin solutions
• Predictive analytics
• Operational intelligence
• Decision-support systems
• Intelligent transportation systems
• Smart city technology
• Mobility solutions
• Geospatial platforms