Manager - AI Solutions Development & Operations

About the role

This role leads the end-to-end development, deployment and operational management of enterprise AI and data science solutions for RTA. It covers vendor partnerships, model lifecycle management and cross-functional integration to deliver secure, high-performance AI, while driving continuous improvement and stakeholder alignment.

Key responsibilities

• Oversee the AI and data science project roadmap, keeping it aligned with approved timelines, standards and strategic objectives.
• Manage vendor selection, qualification and onboarding, and evaluate technical partnerships with AI solution providers and technology vendors.
• Identify and evaluate AI and big data use cases in coordination with the AI Planning Section and business units.
• Manage the full lifecycle of internally developed AI solutions: design, development, testing, deployment, versioning, updates and continuous improvement.
• Monitor vendor performance against service levels and contractual KPIs, and manage service scope, SLAs, performance indicators, business continuity and support arrangements.
• Coordinate integration between internal teams and external vendors, including delivery handovers, knowledge transfer and model deployments with rollback mechanisms.
• Manage model lifecycle (versioning, retraining triggers, re-validation, updates, replacement, decommissioning) and prepare implementation documentation, UAT scenarios and defect tracking.
• Provide technical support, incident management, change execution, user training and feedback management, and monitor usage metrics and outcomes.
• Maintain technical documentation, code repositories, models, reusable assets and operational runbooks.
• Develop and operate AI, data science and analytics solutions, including exploratory data analysis, feature engineering, model training and tuning, within approved environments and platforms.
• Implement acceptance and operational testing, and report on model drift, data quality, cost efficiency and operational incidents.

Required profile

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning or a closely related field from an accredited university.
• 12 years of experience for a Bachelor's degree, 14 years for a Master's degree.
• Proven track record managing the full lifecycle of AI/ML solutions from concept to production operations.
• Demonstrated expertise in vendor management, SLA governance and technical procurement for AI services.

Required skills

• Strong command of MLOps practices and model lifecycle management.
• Knowledge of AI governance frameworks.