AI Architect

Design and architect end-to-end AI solutions that address complex business challenges across the sports, sports performance, education, and healthcare sectors. Develop compelling AI business cases by identifying high-value use cases and leveraging machine learning, natural language processing, computer vision, and advanced data analytics.

Translate business requirements into scalable, secure, and high-performing AI architectures that integrate seamlessly with existing enterprise systems, with a particular focus on sports-specific applications and performance optimization.

Responsibilities

AI Solution Architecture & Delivery:

• Design and implement scalable AI architectures using cloud-native platforms (Azure AI Foundry, Google Agent Space).
• Leverage pre-built AI services (NLP, computer vision, predictive analytics) to accelerate solution delivery.
• Align AI solutions with organizational priorities in sports, healthcare, and education.

Enterprise System & Data Integration:

• Integrate cloud AI services with ERP, CRM, medical, and sports performance platforms.
• Enable connectivity between structured (databases, KPIs) and unstructured (documents, video, medical records) data sources.
• Apply APIs, middleware, and automation tools to streamline data flows and pipelines.

AI Governance & 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 updates from cloud AI providers and implement improvements.

Stakeholder & Client Management:

• Partner with internal stakeholders to identify opportunities for applied AI adoption.
• Demonstrate practical AI solutions with measurable business value.
• Act as a trusted advisor for AI-enabled transformation

Performance & Scalability:

• Optimize applied AI systems for speed, scalability, and reliability.
• Implement monitoring and continuous improvement mechanisms.
• Define KPIs and track ROI of AI deployments

Qualifications

• 8+ years of experience in Solution Architecture with minimum of 4 years of experience in applied AI/ML projects.
• Bachelor's Degree in Computer Science Or Artificial Intelligence, Data Science or Engineering.
• Bilingual (Arabic Speaker) Mandatory

Certifications

• AI Software development related certifications such as MS Certified AI Developer or Architect
• Azure AI Foundry and Google Cloud AI/ML platforms
• Software development related certifications such as MS Certified Developer or Architect

Required Skillsets:

• Expertise in developing AI projects.
• Proficient in AI concepts, tools, frameworks and models.
• Proficient in multiple solution architecture techniques such as conducting architecture evaluation using scenarios, component modelling and impacts analysis
• Proficient in SDLC, requirements analysis, high level and detailed 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 for enterprise-scale knowledge management.
• Skilled in database and data architecture (SQL, NoSQL, vector databases, knowledge graphs).
• Ability to design applied AI systems that are secure, scalable, and performance-optimized.
• Strong communication skills to bridge technical teams and business stakeholders.