Master Works
AI Technical Lead (Enterprise AI Solution Architecture)
- Permanent
- Riyadh, Saudi Arabia
- Experience 2 - 5 yrs
Job expiry date: 23/04/2026
Job overview
Date posted
09/03/2026
Location
Riyadh, Saudi Arabia
Salary
SAR 30,000 - 40,000 per month
Compensation
Job description
The AI Technical Lead (Enterprise AI Solution Architecture) provides end-to-end technical leadership and ownership of AI solution architecture across multiple Artificial Intelligence projects within Nabeh Company. The role is responsible for designing and governing enterprise-grade AI systems and ensuring that AI platforms, AI models, data pipelines, integrations, infrastructure, and security considerations are properly defined from concept design through deployment and operational readiness. The position ensures the correct application of Artificial Intelligence patterns including Computer Vision (CV), Natural Language Processing (NLP), Advanced Analytics, and Large Language Models (LLMs), while evaluating the technical trade-offs between different AI model types, system architectures, and deployment approaches such as cloud deployment, on-premises deployment, and edge deployment. The role plays a key part in ensuring that architectural decisions are scalable, secure, cost-effective, and aligned with enterprise architecture standards as well as client technology requirements. The AI Technical Lead maintains a strong focus on the full AI lifecycle including model development considerations, model deployment strategies, model monitoring processes, and operational readiness of AI systems within enterprise environments. The position collaborates closely with delivery teams, platform teams, infrastructure teams, and integration teams to ensure technical alignment across all AI projects and to guarantee code readiness, release readiness, and environment integration across development stages including Dev, SIT, UAT, and Production (Prod). The role supports delivery execution by assisting Project Managers and Delivery Managers with technical estimations, feasibility assessments, identification of technical risks, technical dependencies, and technical constraints while defining delivery sequencing and technical milestones required for AI project implementation. The AI Technical Lead also reviews technical deliverables to ensure architectural compliance, system quality, and implementation consistency across AI solutions. Additionally, the role translates complex technical architecture decisions into structured communication for non-technical stakeholders and participates in client discussions when architectural clarity or technical assurance related to Artificial Intelligence solutions, AI platforms, and system integrations is required. The position requires hands-on experience delivering enterprise-grade Artificial Intelligence solutions, designing data architectures and AI systems, and implementing integrations across enterprise technology environments while holding AI / ML certifications from Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
Required skills
Key responsibilities
- Lead and own end-to-end AI solution architecture across enterprise Artificial Intelligence projects by defining architecture from concept design through deployment and operational readiness, ensuring AI models, data pipelines, platforms, integrations, infrastructure, and security considerations are properly designed and implemented.
- Design and review comprehensive AI system architectures including data architectures, model pipelines, integration layers, and deployment environments while ensuring solutions remain scalable, secure, cost-effective, and aligned with enterprise architecture standards and client technology requirements.
- Select and implement appropriate Artificial Intelligence patterns including Computer Vision (CV), Natural Language Processing (NLP), Advanced Analytics, and Large Language Models (LLMs) while evaluating technical trade-offs between model types, algorithm architectures, and deployment strategies.
- Evaluate and define deployment strategies for Artificial Intelligence solutions including cloud deployment, on-premises deployment, and edge deployment environments while ensuring compatibility with enterprise infrastructure, security requirements, and operational scalability needs.
- Support Project Managers and Delivery Managers by providing technical estimations, conducting feasibility assessments, identifying technical risks, dependencies, and constraints, and defining delivery sequencing and technical milestones required for successful Artificial Intelligence project execution.
- Drive technical alignment across Artificial Intelligence teams, platform engineering teams, and infrastructure teams while coordinating integration planning and ensuring readiness across development environments including Dev, SIT, UAT, and Production (Prod).
- Review technical deliverables including architecture documentation, AI solution components, data pipeline designs, and integration artifacts to ensure architectural compliance, code readiness, release readiness, solution quality, and consistency across multiple Artificial Intelligence initiatives.
- Translate complex Artificial Intelligence architecture concepts, system integration decisions, and technical trade-offs into structured and clear communication for non-technical stakeholders while participating in client discussions that require architectural clarity and technical assurance.
Experience & skills
- Demonstrate strong hands-on experience delivering enterprise-grade Artificial Intelligence projects and implementing enterprise AI platforms including the design and deployment of AI models, data pipelines, and integrated AI solutions within complex technology environments.
- Possess proven experience in solution architecture covering Artificial Intelligence systems, enterprise data architectures, system integrations, and scalable infrastructure design required for enterprise-level AI solution deployment.
- Demonstrate strong understanding of the complete AI lifecycle including model design considerations, model deployment strategies, model monitoring practices, and operational readiness processes required for production-grade AI systems.
- Show practical experience implementing Artificial Intelligence patterns including Computer Vision (CV), Natural Language Processing (NLP), Advanced Analytics, and Large Language Models (LLMs) while selecting appropriate AI architectures and deployment strategies.
- Demonstrate experience evaluating and selecting deployment environments including cloud deployment, on-premises deployment, and edge deployment approaches while balancing scalability, cost optimization, and infrastructure performance requirements.
- Possess the ability to provide technical estimations, conduct feasibility assessments, identify technical risks and dependencies, and support delivery planning activities that enable successful coordination between solution architecture and project delivery teams.
- Hold an AI / Machine Learning certification from Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP) demonstrating formal technical qualification in Artificial Intelligence and Machine Learning platform technologies.
- Demonstrate proficiency in Arabic language with strong spoken and written English communication skills while supporting client discussions, architectural reviews, and stakeholder communication within enterprise AI projects.