AI Architect

Role Overview

Ai Solution Architecture & Delivery

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

Enterprise System & Data Integration

• Integrate cloud-based AI services with enterprise systems such as ERP, CRM, medical, and sports performance platforms.
• Enable seamless connectivity between structured data (databases, KPIs) and unstructured data (documents, video, medical records).
• Utilize APIs, middleware, and automation tools to streamline data pipelines and workflows.

Ai Governance & Risk Management

• Ensure compliance with data protection regulations such as GDPR, HIPAA, and relevant local laws.
• Monitor AI systems for bias, transparency, and explainability.
• Implement security, governance, and ethical AI best practices.

Applied Ai Enablement

• Deploy and customize existing AI models for practical, real-world applications.
• Configure conversational AI, knowledge agents, and analytics tools to support business operations.
• Continuously evaluate advancements in AI platforms and implement enhancements.

Stakeholder & Client Management

• Collaborate with internal stakeholders to identify opportunities for AI adoption.
• Present AI solutions with clear, measurable business value.
• Act as a trusted advisor for AI-driven transformation initiatives.

Performance & Scalability

• Optimize AI systems for performance, scalability, and reliability.
• Establish monitoring frameworks and continuous improvement processes.
• Define KPIs and track ROI for AI implementations.

Qualifications & Experience

• Minimum 8+ years of experience in Solution Architecture.
• At least 4 years of hands-on experience in applied AI/ML projects.
• Mandatory: Bilingual (Arabic speaker)

Education

• Bachelor’s Degree in Computer Science, Artificial Intelligence, Data Science, IT, or Engineering.

Certifications

• AI-related certifications such as Microsoft Certified AI Developer/Architect.
• Experience with Azure AI Foundry and Google Cloud AI/ML platforms.
• Additional software development certifications (e.g., Microsoft Certified Developer/Architect) are a plus.

Required Skills & Competencies

• Strong expertise in designing and delivering AI-driven solutions.
• Proficiency in AI concepts, tools, frameworks, and models.
• Experience with solution architecture methodologies, including evaluation techniques, component modeling, and impact analysis.
• Solid understanding of SDLC, requirements analysis, and technical design (high-level and detailed).
• Hands-on experience with Azure AI Foundry for enterprise AI lifecycle management.
• Expertise in Google Agent Builder, SDKs for mobile agents, and multi-agent systems.
• Strong knowledge of Advanced Retrieval-Augmented Generation (RAG) for enterprise knowledge systems.
• Proficiency in data and database architecture (SQL, NoSQL, vector databases, knowledge graphs).
• Ability to design secure, scalable, and high-performance AI systems.
• Excellent communication skills to bridge technical and business stakeholders.