The Manager, AI Factory & Future Tech will be responsible to establish and operate Qatar Foundation’s AI Factory, ensuring that AI and digital use cases are validated, productized, and scaled for enterprise adoption. And to oversee the exploration and validation of frontier technologies through an embedded Future Tech Lab. The position is responsible for the full lifecycle of AI Ops and LLM Ops — including deployment, monitoring, observability, governance, and continuous improvement — ensuring safe, reliable, and responsible AI operations across the enterprise.

Key Result Areas:

• Lead the AI/ML lifecycle: ideation, prototyping, validation, productisation, and enterprise adoption.
• Manage AI Ops, including deployment pipelines, monitoring, incident management, observability, and continuous optimisation.
• Oversee LLM Ops, including prompt lifecycle management, governance, safety guardrails, red-teaming, rollback, and model evaluation.
• Align AI initiatives with QF’s enterprise data platforms, governance frameworks, and security standards.
• Collaborate with Change & Adoption and Programme Delivery to drive adoption and measurable value delivery.
• Operate a sandbox environment to explore and validate emerging technologies (e.g., advanced AI models, agentic AI, IoT/AI convergence, immersive technologies).
• Lead prototyping, validation, and limited pilots in collaboration with QF AI Hub, HBKU, and research partners.
• Define pathways for validated pilots to transition into the AI Factory for scaling and enterprise adoption.
• Provide foresight on technology trends, risks, and opportunities to inform QF’s digital strategy.
• Enforce compliance with QF AI policy, international standards, and responsible AI practices across AI Ops and LLM Ops.
• Provide transparent reporting on AI Factory outcomes, adoption metrics, and realised value.
• Contribute to enterprise digital and data architecture, ensuring effective integration of AI and future technologies.
• Other reasonable tasks as assigned by supervisor.

Minimum Knowledge, Skills & Experience:

• Bachelor’s degree in computer science, Data Science, Engineering, or a related field, Masters is preferred.
• Professional certifications in AI/ML Ops, cloud platforms, or responsible AI desirable.
• 8 - 10 years of full-time relevant work experience in digital transformation, enterprise IT, or AI/ML delivery, with increasing leadership responsibility.
• Proven record of scaling AI/ML solutions from prototype to enterprise deployment.
• Hands-on expertise with AI Ops / MLOps frameworks (e.g., CI/CD for models, observability, registries, feature stores).
• Practical experience with LLM Ops from recent projects, including prompt management, safety guardrails, evaluation, and rollback.
• Strong exposure to cloud-native environments, data engineering, or enterprise platforms.
• Experience managing emerging technology pilots and integrating validated innovations into enterprise adoption.
• Strong technical knowledge of AI/ML lifecycle management, AI Ops, and LLM Ops.
• Ability to balance innovation with operational discipline.
• Excellent communication and stakeholder management skills.
• Strong leadership and cross-functional collaboration capabilities.
• Excellent writing skills with the ability to draft and edit a variety of written reports and communications and to articulate ideas clearly and concisely; Arabic proficiency is an advantage
• Proficiency in MS Office applications