AI Architect
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Key skills for this role
Role Overview
Design and architect end-to-end AI solutions for complex business challenges across sports, sports performance, education, and healthcare.
Develop AI business cases by identifying high-value use cases and applying machine learning, natural language processing, computer vision, and advanced data analytics.
Translate business requirements into scalable, secure, and high-performing AI architectures focused on sports applications and performance optimization.
Key Skills for This Role
Full Job Posting
Role Overview
Design and architect end-to-end AI solutions for complex business challenges across sports, sports performance, education, and healthcare.
Develop AI business cases by identifying high-value use cases and applying machine learning, natural language processing, computer vision, and advanced data analytics.
Translate business requirements into scalable, secure, and high-performing AI architectures focused on sports applications and performance optimization.
AI Solution Architecture and Delivery
- Design and implement scalable AI architectures using Azure AI Foundry and Google Agent Space.
- Use pre-built natural language processing, computer vision, and predictive analytics services to accelerate solution delivery.
- Align AI solutions with organizational priorities in sports, healthcare, and education.
Enterprise Systems and Data Integration
- Integrate cloud AI services with ERP, CRM, medical, and sports performance platforms.
- Connect structured data such as databases and KPIs with unstructured data such as documents, video, and medical records.
- Use APIs, middleware, and automation tools to streamline data flows and pipelines.
AI Governance and Risk Management
- Ensure compliance with GDPR, HIPAA, and local data regulations.
- Monitor AI systems for bias, transparency, and explainability.
- Apply security and governance best practices in AI deployment.
Applied AI Enablement
- Deploy and customize existing AI models for real-world use cases.
- Configure conversational AI, knowledge agents, and analytics tools to support operations.
- Evaluate cloud AI provider updates and implement improvements.
Stakeholder and Performance Management
- Partner with internal stakeholders to identify opportunities for applied AI adoption.
- Demonstrate practical AI solutions with measurable business value and advise on AI-enabled transformation.
- Optimize AI systems for speed, scalability, and reliability, while monitoring improvements and tracking KPIs and ROI.
Qualifications
- At least eight years of solution architecture experience, including at least four years in applied AI or machine learning projects.
- A bachelor's degree in computer science, artificial intelligence, data science, engineering, or a related field.
- Arabic language ability is mandatory.
Required Skillsets
- Expertise in AI projects, concepts, tools, frameworks, and models.
- Proficiency in solution architecture evaluation, component modeling, impact analysis, SDLC, requirements analysis, and technical design.
- Proficiency in Azure AI Foundry for enterprise AI deployment and lifecycle management.
- Hands-on expertise with Google Agent Builder, Google SDK for mobile agents, and multi-agent systems.
- Strong knowledge of Advanced RAG, database and data architecture, SQL, NoSQL, vector databases, and knowledge graphs.
- Ability to design secure, scalable, and performance-optimized applied AI systems with strong stakeholder communication.
Certifications and Platforms
- AI software development certifications such as Microsoft Certified AI Developer or Architect are identified as relevant.
- Azure AI Foundry and Google Cloud AI/ML platforms are identified under the certifications and platform requirements.
- Software development certifications such as Microsoft Certified Developer or Architect are identified as relevant.
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