Key Responsibilities:

• AI Strategy & Consultancy: Act as a senior consultant to identify and assess AI use cases, evaluating them for business value, technical feasibility, and architectural fit within the digital transformation roadmap.
• Architecture Design: Architect and oversee the deployment of end-to-end AI stacks using Azure AI Foundry and on-premise enterprise solutions. This includes designing for Inference Engines, Vector Databases, and Agent Builders.
• Sizing & Cost Estimation: Perform detailed technical sizing of AI infrastructure (Compute/GPU/Token usage) and provide accurate cost-benefit analysis for both Azure cloud and on-premise implementations.
• Agentic & Gen-AI Leadership: Lead the design and implementation of Agentic-AI workflows and Multi-Agent Systems, ensuring robust orchestration and goal-alignment. LLM Finetuning for Arabic language is also needed.
• Operations (MLOps/LLMOps/AgentOps): Establish and enforce standards for the AI lifecycle, focusing on automated deployment, monitoring of agentic behavior, and model performance optimization.
• Hybrid Integration: Design architectures that bridge on-premise data security with Azure AI capabilities, ensuring seamless data flow between the AI stack and the Medallion data architecture.
• Compliance & Governance: Ensure all AI architectures comply with federal AI ethics guidelines, focusing on data privacy and responsible AI.
• Technical Troubleshooting: Resolve complex issues related to model latency, vector embedding quality, and integration bottlenecks within the AI pipeline.
• Leadership & Mentoring: Guide AI engineers and data scientists, fostering a culture of excellence in all data activities.

Qualifications:

• Certifications:Microsoft Azure AI Engineer Associate and Azure Solutions Architect Expert certification.
• Experience: Minimum of 8 years in AI/Machine Learning, with at least 3 years in a Lead Architect capacity for large-scale enterprise projects.
• Hands-on Mastery: Deep experience with Azure AI Foundry, Vector Databases (e.g., Weaviate, Azure AI Search, vLLM), and Inference Engines (e.g., Nvidia Triton, vLLM, etc)
• Advanced AI Paradigms: Proven track record in delivering Agentic-AI and Generative AI solutions at an enterprise level.
• Technical Stack: Proficiency in AI and ML frameworks, Python, Agentic Workflow, and containerization (Kubernetes/Docker).
• Consultancy Skills: Strong ability to translate complex AI concepts into architectural blueprints and financial estimates for stakeholders.
• Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
• Language: Proficiency in Arabic and English is required

Competencies:

• AI Technical Leadership: Ability to set the vision for the AI stack.
• Financial Acumen: Proficiency in AI cost modeling (Tokenomics & Infrastructure).
• Analytical Thinking: Breaking down business problems into AI-solvable components.
• Collaboration: Working closely with the Data Architect Lead to leverage enterprise data for AI.
• Adaptability: Staying ahead of the rapidly evolving AI landscape