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Job Description & How to Apply Below
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.
- 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.
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.
- 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.
- 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
- Optimize applied AI systems for speed, scalability, and reliability.
- Implement monitoring and continuous improvement mechanisms.
- Define KPIs and track ROI of AI deployments
- 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
- 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
- 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, No
SQL, 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.
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