مهندس معماري ذكاء اصطناعي أول (Principal AI Architect)

Job Summary

The Principal AI Architect leads the AI aspects of assigned programs from requirements through to deployment, ensuring technical delivery and stakeholder engagement. This role involves designing AI/ML solutions, data architecture, and integration with business systems.

Responsibilities

• Manage the AI components of programs end to end, including architecture, development, integration, and deployment.
• Prioritize AI use cases based on business value and feasibility, and develop achievable delivery plans.
• Serve as the main technical contact during stakeholder and working sessions to build trust and credibility.
• Design the data infrastructure needed to support AI use cases, including ingestion, storage, and quality.
• Choose and design AI/ML methods such as text classification, machine translation, similarity search, LLM assistants, forecasting, and decision-support scoring.
• Plan integration of AI outputs into core business systems for production use within workflows.
• Develop priority AI models and pipelines directly and oversee engineering support as needed.
• Implement MLOps practices appropriate to program scale, including versioning, CI/CD, and monitoring.
• Validate AI models against success metrics and prepare evidence for stakeholder approval at milestones.
• Ensure AI solutions comply with responsible AI principles, data governance, privacy, explainability, and audit logging.
• Identify and escalate technical risks, gaps, and scope trade-offs to stakeholders and leadership.
• Translate business and policy requirements into defined technical work and communicate scope, timeline, and resource trade-offs clearly.

Requirements

• 8 – 11 years of experience in AI/ML engineering and architecture.
• Proven experience leading AI solution delivery from design to production as a lead architect or principal engineer.
• Knowledge of AI/ML techniques including NLP, text classification, machine translation, similarity search, LLM assistants, and forecasting.
• Experience designing and operating data pipelines such as ETL/ELT and lakehouse environments for AI use cases.
• Strong skills in stakeholder communication, scoping, prioritization, and managing delivery trade-offs.
• Experience in regulated, public-sector, or specialized domains is advantageous.
• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field; advanced degrees are a plus.

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