AI Technical Lead

Provide end-to-end AI technical leadership and solution architecture ownership across AI Projects. The role ensures sound architectural decisions, correct application of AI patterns, and delivery-ready designs, while reducing technical dependency on Project Managers and strengthening execution alignment across delivery teams.

Key Responsibilities

Architecture & Technical Leadership

• Own and lead AI solution architecture across projects, from concept design through deployment and operational readiness.
• Define and review end-to-end solution architectures, including AI models, data pipelines, platforms, integrations, infrastructure, and security considerations.
• Ensure architectural decisions are scalable, secure, cost-effective, and aligned with enterprise and client standards.

AI Pattern & Technology Selection

• Ensure the correct selection and implementation of AI patterns, including:
• Computer Vision (CV)
• Natural Language Processing (NLP)
• Advanced Analytics
• Large Language Models (LLMs)
• Evaluate trade-offs between model types, architectures, and deployment approaches (cloud, on-prem, edge).

Delivery & PM Enablement

• Support Project Managers and Delivery Managers with:
• Technical estimations and feasibility assessments
• Identification of technical risks, dependencies, and constraints
• Delivery sequencing and technical milestone definition
• Act as the technical reference point to unblock delivery and reduce escalation cycles.

Platform, Integration & Readiness

• Drive technical alignment across AI teams, platform teams, and infrastructure teams.
• Ensure code readiness, release readiness, and integration planning across environments (Dev, SIT, UAT, Prod).
• Review technical deliverables to ensure quality, consistency, and architectural compliance.

Stakeholder Communication

• Translate complex technical decisions into clear, structured communication for non-technical stakeholders.
• Participate in client discussions where architectural clarity or technical assurance is required.

Qualifications & Requirements

·       Strong hands-on background in delivering enterprise-grade AI projects and AI platforms.

·       Proven experience in solution architecture, including AI systems, data architectures, and system integrations.

·       Solid understanding of AI lifecycle, model deployment, monitoring, and operational considerations.

·       Ability to balance technical depth with delivery practicality.

Required Certifications

AI / ML certification from Azure, AWS, or GCP (mandatory or strong requirement).

Arabic speaker with strong spoken and written English.

·  Immediate joining preferred.