Head of Generative AI and Innovation

The Digital Transformation Office (DTO) is a strategic division within the corporate group dedicated to driving and overseeing digital transformation initiatives across IMDA. The DTO plays a pivotal role in developing and implementing comprehensive strategies that align with IMDA’s goals and objectives through the innovative use of emerging technology and data. By spearheading digital transformation initiatives, the DTO aims to revolutionize processes, elevate customer experiences, and foster a culture of innovation. Through collaboration with various departments, the DTO ensures that digital initiatives are integrated seamlessly across the organization, positioning IMDA to be at the forefront in the digital age.
Role Overview
The Head of Generative AI and Innovation will lead the strategic development and implementation of frontier Generative AI solutions across the organization. This role involves overseeing Generative AI team, forging innovation and driving the integration of generative AI technologies into products, processes, and services.

Responsibilities

1. Strategy & Leadership

• Define and drive the organization’s vision and strategy for generative AI, ensuring alignment with overall business objectives.
• Identify opportunities for innovation and business value creation through AI-driven insights and solutions.
• Develop and maintain a roadmap for AI adoption, piloting initiatives, and driving adoption across various business units.

2. Solution Development & Implementation

• Lead cross-functional teams of data scientists, engineers, product managers, and domain experts to design, build, and deploy generative AI-driven solutions that address key business challenges.
• Develop and maintain an enterprise-wide Generative AI platform, ensuring it is scalable, secure, compliant, and easily accessible to different business units.
• Oversee large-scale AI projects, ensuring technical feasibility, budget management, and timely delivery.
• Guide the development of proof-of-concepts (PoCs) and MVPs, creating scalable AI solutions that can be integrated into the organization’s technology stack.

3. Team Building & Management

• Attract, hire, and retain top AI talent, developing an environment that fosters creativity, collaboration, and continuous learning.
• Coach and mentor team members, providing professional development opportunities and skill-building initiatives.
• Establish agile project management practices, promoting high efficiency, accountability, and transparency.

4. Stakeholder Engagement

• Collaborate with senior leadership, department heads, and external partners to identify business needs and evaluate AI solution viability.
• Communicate complex AI concepts in clear, business-oriented language to stakeholders at all levels.
• Build and maintain relationships with technology vendors, business lines and other external parties for potential partnerships and co-innovation projects.

5. Governance & Ethics

• Define and implement best practices for AI ethics, data privacy, and responsible AI governance.
• Ensure compliance with relevant regulations and internal policies.
• Establish standards and guidelines for model deployment, monitoring, and risk management.

6. Performance Measurement & Continuous Improvement

• Develop KPIs and metrics to measure the success, impact, and ROI of AI initiatives.
• Implement processes for ongoing evaluation and optimization of AI models and processes.
• Cultivate a data-driven culture and champion continuous improvement across all AI-related activities.

Requirements

• Education
  • Background in computer science, Machine Learning, Data Science, or a related field preferred. Equivalent experience in AI leadership and innovation may be considered.
• Experience
  • 10+ years of experience in AI/ML, data science, or a similar field, with at least 5 years in a leadership role.
  • Proven track record of delivering AI solutions (particularly generative models) in complex, high-impact environments.
  • Experience managing cross-functional teams and large-scale, transformational projects.
• Technical Expertise
  • Proficiency in machine learning, deep learning, NLP, computer vision, and other AI domains.
  • Familiarity with the latest generative AI architectures (e.g., Transformer-based models, diffusion models, etc.) and large-language-model frameworks.
  • Experience with cloud-based AI platforms (AWS, Azure, GCP) and relevant ML frameworks (TensorFlow, PyTorch, etc.).
  • Demonstrated experience in building or integrating AI platforms in an enterprise setting.
• Business Acumen
  • Strong understanding of how AI can drive business value, with the ability to connect technical capabilities to strategic objectives.
  • Experience in budgeting, project planning, and managing vendor relationships.
  • Adept at quantifying business impact and ROI of AI initiatives.
• Leadership & Soft Skills
  • Exceptional communication skills, capable of translating complex technical topics into business language.
  • Demonstrated ability to lead, motivate, and mentor high-performing teams.
  • Strong problem-solving and decision-making abilities with a track record of managing ambiguity.
  • Collaborative mindset, capable of building consensus among diverse stakeholders.

Key Competencies

• Strategic Thinking: Ability to set a clear vision for AI initiatives that align with overall business goals.
• Innovation & Creativity: Comfortable exploring novel approaches and challenging the status quo.
• Execution Excellence: Track record of taking AI concepts to production, with a focus on quality and scalability.
• Change Management: Skilled in driving organizational change, influencing culture shifts, and instilling a data-driven mindset.
• Risk Management: Adept at identifying and mitigating technical, ethical, and compliance-related risks.
• Collaboration & Influence: Strong interpersonal skills to forge partnerships with internal and external stakeholders.

#LI-IT2