Chief Specialist - AI Solutions Quality Assurance - Model Validation

Job Purpose Establish and enforce quality assurance standards, governance frameworks, and compliance controls for AI solutions across the full model lifecycle. Define risk-based quality gates, validation protocols, and fairness criteria to ensure RTA's AI deployments meet regulatory, ethical, and operational excellence benchmarks. Drive continuous improvement in AI solution quality through rigorous technical verification,post-launch monitoring, and cross-functional collaboration with development, operations, and regulatory stakeholders.Roles and Responsibilities Strategy Develop and periodically update the AI Solutions Quality Assurance framework, including quality standards,technical specifications, engineering specifications, and approval gate criteria aligned with RTA's AI governance policies, regulatory requirements, and industry best practices.Define risk-based quality requirements for AI solutions encompassing traceability, explainability, fairness,privacy, security, safety, and reliability, and embed these into the AI model lifecycle governance structure.Prepare and submit AI quality policies, procedures, guidelines, and templates to the Center Director for approval, ensuring alignment with the Authority's digital strategy, Dubai Data Law, and applicable regulatory mandates.Identify and maintain compliance and audit requirements related to AI solutions in coordination withrelevant regulatory bodies and internal governance teams, ensuring RTA's AI portfolio remains audit-readyat all timeConduct quarterly risk reviews of AI quality assurance processes, identifying emerging risks in modelgovernance, bias, and compliance, and submit mitigation recommendations to the Center Director.Operations Conduct initial technical verification of AI solutions prior to go-live, including validation of technical documentation completeness, resolution of quality and assurance findings, and confirmation of readiness for production deployment.Execute fairness and bias reviews of AI solutions and material model changes before and after launch,issuing formal results, recommendations, and go/no-go decisions for deployment.Review technical designs of AI solutions from a quality, compliance, and standards-conformance perspective, coordinating with relevant stakeholders and departments to ensure alignment with institutional requirements.Apply and enforce User Acceptance Testing (UAT) guidelines in coordination with the Development and Operations sections, ensuring all AI solutions meet predefined acceptance criteria before release.Define and implement post-launch model performance monitoring requirements, including KPIs, model drift detection thresholds, incident boundaries, and escalation protocols.Define model change governance requirements covering re-validation, retraining triggers, change management procedures, and model decommissioning criteria.Monitor compliance with AI quality standards and controls by internal teams, implementation partners, and service providers, and track corrective action plans for any identified non-compliance.Exercise 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 evidence, responses, and feedback associated with internal and external audit tasks and regulatory oversight activities, ensuring timely and accurate submissions.Raise awareness and provide guidance on AI quality standards, governance controls, and best practices to business owners, technical teams, and implementation partners, supplying necessary templates and toolkits for application.Provide clerical support including scanning, archiving, and organizing documents while ensuring information security measures are applied.Coordinate with HR for employee-related requests (leaves, training, certificates, resignations, etc.).Product / Process Improvement Develop and apply UX/UI guidelines specific to AI solutions in coordination with the Development and Operations sections, ensuring user-centric design standards are met across all AI deployments.Prepare continuous improvement plans for AI quality assurance processes, submitting proposals for process optimization, tooling enhancements, and benchmarking against industry-leading practices.Analyze periodic quality surveys and audit findings, identify gaps and areas for improvement in AI solution delivery, and submit final recommendations for approval by the Center Director.Research and evaluate emerging AI quality assurance methodologies, automated validation tools, and governance technologies, integrating lessons learned into evolving QA frameworks to ensure scalable and responsible AI deployment across RTA.Coordinate with relevant partners to develop, improve, and measure the effectiveness of AI quality assurance systems, contributing to the Authority's digital excellence objectives.

Qualifications

Education: Bachelor's degree in Computer Science, Information Systems, or a related technical field.Experience: Minimum 9 years of progressive professional experience in AI/ML quality assurance, model governance, or related technical fields in case of a Master's degree; minimum 11 years in case of a Bachelor's degreeQualification: Professional certification in AI governance, data governance (e.g., DAMA-CDGA), or quality management (e.g., CQI, ISO 9001 Lead Auditor) is advantageous