AI Technical Lead - Arabic speaker
Listed on 2026-03-04
-
IT/Tech
AI Engineer, Systems Engineer, Cloud Computing, Data Engineer
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.
· 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 CertificationsAI / ML certification from Azure, AWS, or GCP (mandatory or strong requirement).
Arabic speaker with strong spoken and written English
.
·
Immediate joining preferred.
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