Executive Director, AI Tech Lead

About Mizuho Bank Singapore

Mizuho Bank Singapore Branch, a subsidiary of the globally ranked 15th largest bank, Mizuho Financial Group based in Tokyo, has been a key player in the Asia-Pacific region for over 50 years. Operating under a Full Bank License, it supports more than 2,000 corporate clients—both Japanese and international—offering comprehensive financial services including corporate finance, trade finance, cash management, project finance, and treasury. The bank also collaborates with Mizuho Securities to provide investment banking solutions. The branch functions as a regional hub supporting APAC operations with around 1,000 staff members.

Role Overview

The Executive Director serving as AI Tech Lead will spearhead the architecture, implementation, and governance of enterprise-scale AI and Generative AI (GenAI) solutions within a highly secure, regulatory-compliant banking environment. Leading a multidisciplinary team, you will design explainable, ethical AI systems suitable for production on-premise platforms and dynamic cloud-based prototypes on Azure, bridging innovation with stringent operational risk management.

Key Duties

• Direct the end-to-end design and rollout of AI and GenAI solutions targeted at banking-specific use cases, progressing from pilot phases to production-ready minimum viable products.
• Oversee secure deployment and orchestration of AI models across hybrid infrastructures using Kubernetes, GPU clusters, and secure networking technologies for production environments; concurrently manage cloud-based Azure settings for experimental and prototyping purposes.
• Integrate AI workflows into legacy banking systems and modern cloud frameworks while enforcing compliance with responsible AI practices, including explainability and regulatory mandates.
• Provide mentorship to engineers and data scientists throughout the AI deployment lifecycle, and foster organizational growth via training programs and workshops for IT teams.
• Stay abreast of emerging AI frameworks, architectures, and automation practices, encouraging a culture that balances experimentation with responsible adoption.

Essential Skills and Qualifications

• A Bachelor’s degree or higher in Computer Science, IT, Statistics, Mathematics, or a related quantitative discipline.
• Over 10 years of software engineering experience with a minimum of 4 years focused on leading AI and ML projects within corporate or fintech settings.
• Proven expertise in architecting, deploying, and managing enterprise GenAI solutions across hybrid (on-premise and cloud) environments.
• Advanced proficiency in Python coding for developing scalable and maintainable AI/GenAI software.
• Hands-on experience with machine learning and GenAI frameworks, including but not limited to PyTorch, TensorFlow, and Scikit-learn, as well as GenAI orchestration tools suitable for enterprise scale.
• Strong knowledge of Kubernetes, Docker, GPU orchestration, MLflow, Kubeflow, Databricks, and Azure Machine Learning for AI lifecycle and infrastructure management.
• Expertise in securing and automating AI model training, CI/CD pipelines, version control, monitoring, and compliance.
• Skills in designing and optimizing data engineering pipelines for high compliance, including ETL orchestration and handling NoSQL and large-scale data systems.
• In-depth understanding of AI ethics, explainability, bias mitigation, data privacy, and regulatory compliance within financial services.
• Solid insight into financial products, market operations, and risk management to tailor AI applications effectively.
• Strong communication skills to translate technical AI concepts to diverse stakeholders, including senior leaders and non-technical teams.
• Experience in leading organizational change initiatives to integrate AI workflows into traditional banking operations and foster trust in automated decision processes.