AI Architect - Qatar

Full Description

Job Summary (List Format):

• Design and deliver end-to-end AI solutions focused on sports, sport performance, education, and medical sectors.

• Develop 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 implementation.

• Integrate AI solutions with enterprise systems (ERP, CRM, medical, and sports performance platforms) and manage both structured and unstructured data sources.

• Ensure compliance with data regulations (GDPR, HIPAA, etc.), and implement AI governance, security, and risk management best practices.

• Deploy, customize, and optimize AI models for real-world applications; monitor system performance, scalability, and reliability.

• Serve as a liaison and advisor to internal stakeholders and clients, identifying opportunities for AI adoption and demonstrating measurable business value.

• Track and report on KPIs and ROI for AI deployments.

• Stay updated on advancements from cloud AI providers and implement relevant system improvements.

• Collaborate with cross-functional teams, bridging technical and business requirements.

Qualifications:

• 8+ years of experience in Solution Architecture, with at least 4 years in applied AI/ML projects.

• Bachelor's degree in Computer Science, AI, Data Science, IT, or Engineering.

• Relevant certifications (e.g., MS Certified AI Developer/Architect, Azure AI Foundry, Google Cloud AI/ML platforms).

Required Skills:

• Proven expertise in developing and deploying AI projects.

• Proficiency in AI concepts, tools, frameworks, and models.

• Strong solution architecture skills, including architecture evaluation, component modeling, and impact analysis.

• Proficient in SDLC, requirements analysis, and both high-level and detailed technical design.

• Advanced proficiency in Azure AI Foundry and Google Agent Builder for enterprise AI deployment.

• Knowledge of Advanced RAG for knowledge management, and experience with SQL, NoSQL, vector databases, knowledge graphs.

• Ability to design secure, scalable, and high-performance AI systems.

• Excellent communication skills for interfacing with technical and non-technical stakeholders.