Manager - AI Solutions Quality Assurance

Lead the AI Solutions Quality Assurance function within the Artificial Intelligence & Data Science

Department, ensuring all AI solutions meet established quality, governance, and compliance standards throughout their lifecycle.

Oversee the development and enforcement of AI quality frameworks, risk-based assessment protocols, and control gates that safeguard fairness, explainability, security, and reliability.

Drive continuous improvement in AI model validation, post-deployment monitoring, and regulatory compliance to uphold RTA's commitment to ethical and trustworthy artificial intelligence.

Roles and Responsibilities

• Lead, Develop, maintain, and periodically update the Authority's AI quality assurance frameworks, policies,
• technical standards, and engineering specifications in alignment with RTA's approved requirements,regulatory mandates, and international best practices for AI governance and ethics.
• Lead Define and enforce risk-based requirements for AI solutions, encompassing traceability, explainability,
• fairness, privacy, security, safety, and reliability, ensuring all AI initiatives meet the Authority's risk appetite and compliance obligations.
• Manage establish and maintain quality standards and control gates (approval checkpoints) across all stages of the AI model lifecycle, from design and development through deployment and retirement, ensuring structured progression and accountability at each phase.
• Oversee the implementation of AI model quality assurance frameworks, including validation methods, acceptance thresholds, evidence requirements, and independent review roles, to ensure rigorous and consistent model assessment.
• Lead the development and periodic review of AI governance and ethics policies, ensuring alignment with the UAE National AI Strategy, Dubai Government directives, and RTA' institutional standards for responsible AI deployment.
• Monitor and ensure compliance with AI quality standards and controls by internal teams, implementation partners, and service providers, tracking corrective actions and escalation of non-compliance to senior leadership.
• Ensure Coordinate with relevant internal departments and external regulatory bodies to identify, document, and manage AI-related compliance and audit requirements, ensuring RTA meets all regulatory obligations.
• Ensure Develop and deliver AI quality awareness programs, guidance, and toolkits for business owners,
• technical teams, and implementation partners to foster a culture of quality and compliance across the AI ecosystem.

• Manage conduct pre-launch technical verification of AI solutions, including validation of technical documentation completeness, resolution of quality and assurance findings, and confirmation of readiness for operational deployment.
• Manage Execute fairness reviews and material change assessments on AI models before and after launch, issuing formal results, recommendations, and go/no-go decisions for solution deployment.
• Ensure Apply and enforce AI model quality assurance frameworks, monitoring model performance, validating outputs against defined acceptance criteria, and ensuring independent review processes are followed.
• Ensure follow and enforce User Acceptance Testing (UAT) guidelines in coordination with the Development and Operations Section, ensuring all AI solutions undergo structured and documented acceptance testing prior to go-live.
• Manage define and monitor post-launch model performance requirements, including key performance indicators, model drift detection thresholds, and incident boundaries, ensuring continuous operational quality.
• Manage define and enforce model change governance requirements, including re-validation triggers, retraining protocols, change management procedures, and model deactivation criteria when performance or compliance thresholds are breached.
• Ensure exercise and enforce contractual audit rights over implementation partners and service providers developing or operating AI models, including access to model documentation, data lineage, and evaluation evidence for independent verification.
• Manage and maintain audit evidence, responses, and feedback related to AI quality assurance tasks and regulatory oversight activities, ensuring timely and accurate submission to internal and external auditors.
• Monitor the compliance of internal teams, implementation partners, and service providers with AI quality standards and controls, tracking and following up on corrective actions when non-compliance is identified.

• Ensure review technical designs of AI solutions from a quality, compliance, and verification perspective,validating alignment with institutional standards and relevant requirements in coordination with stakeholders and concerned departments.
• Manage develop and implement User Experience (UX) and User Interface (UI) guidelines specific to AI solutions in coordination with the Development and Operations Section, ensuring user-centric quality in AI interactions.
• Ensure prepare and implement continuous improvement plans for AI quality assurance processes, submitting proposals for ongoing development initiatives and leading changes based on best practices, benchmarking, and lessons learned.
• Ensure analyze periodic quality surveys and performance data in coordination with organizational units,identifying gaps and areas for improvement, and submitting final recommendations for approval by the Director.
• Ensure prepare and follow up on the implementation of plans to review and update AI quality assurance services, procedures, and systems in line with quality management system requirements, submitting necessary recommendations for continuous development.
• Ensure conduct horizon scanning of emerging AI quality assurance methodologies, regulatory
• developments, and industry best practices to proactively update the Authority's QA frameworks and standards.

• The role is primarily office-based, with duties carried out within a standard office environment. The positionrequires regular interaction with cross-functional teams, participation in review boards, and coordination with external partners through virtual and in-person meetings.

:

• Education:

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science,Software Engineering, or a closely related technical field from an accredited university.

• Experience:

12+ years of progressive professional experience in case of a Master's degree (14+ years in case of a Bachelor's degree)

• Qualification:

Demonstrated expertise in AI model lifecycle management, quality assurance frameworks, and AI governance standards.

Proven ability to define and enforce technical quality standards, control gates, and compliance protocols for AI solutions.