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Vacancy
1 Vacancy
Job Description
Roles & Responsibilities
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 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.
Desired Candidate Profile
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
Company Industry
- Defence
- Military
- Government
Department / Functional Area
- IT Software
Keywords
- Manager
- AI Factory & Future Tech
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https://fa-eolw-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX/job/2812
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