The Head of AI Factory is responsible for shaping and executing the organization's data science and artificial intelligence (AI) strategy. This role leads the development and deployment of advanced analytics, machine learning models, and data-driven solutions that enable smarter decision-making, improve risk management, and enhance customer experiences. The Head of AI Factory acts as a trusted advisor to senior executives and drives a culture of innovation and data-driven decision-making across the organization
I. Job Description
1. Strategic Leadership
- Define and implement the enterprise-wide data science and AI strategy aligned with business priorities.
- Advise C-level executives on opportunities to leverage data for business growth, risk mitigation, and operational efficiency.
- Expand usage & best practices of AI to subsidiary companies
2. AI Model Development & Innovation
- Lead Predictive AI development (forecasting, scoring, optimization, recommendation, anomaly detection) with strong data/feature engineering and model lifecycle management.
- Lead Generative AI initiatives (LLMs, RAG, agents, domain fine-tuned models), including prompt frameworks, knowledge integration, and safety guardrails.
- Architect model solutions—choose between build, fine-tune, RAG, prompt engineering, or third-party models based on business, cost, risk, and performance trade-offs.
- Oversee MLOps & LLMOps pipelines, ensuring scalable deployment, versioning, CI/CD, monitoring, and automation for both predictive and generative models.
- Create reusable AI assets & platforms: feature stores, vector DBs, prompt libraries, embeddings, model registries, inference APIs, and agent orchestration frameworks
3. Technology Architecture
- Collaborate with IT division & Data Architecture to build scalable data platforms, pipelines, and AI/ML infrastructure for both ML & GenAI, supporting both batch & real time flow
- Drive experimentation & RnD to catch up with practical emerging AI technologies
4. Governance & Compliance
- Establish ethical AI practices and ensure compliance with data privacy, regulatory, and security requirements.
5. Business partnership
- Partner with business units to consult about the application of AI/GenAI for business
- Collaborate with business & product owners to define problem statements, estimate value, build ROI and impact models, and measure post-deployment outcomes
6. People Management
- Implement the necessary leadership and management to enable direct and indirect subordinates to achieve the goals of the AI Factory.
- Head-count planning, human resource allocation. Work in collaboration with HR to develop recruitment, training, succession planning, career development roadmap, recognition employees, performance management for employees in the Department
- Develop talent and organizational capability in AI/GenAI, providing coaching and leadership to team members and create future leaders within the organization.
7. Corporate Culture
- Act as a role model in building corporate culture. Ensure the correct and full implementation of corporate culture implementation plans; Employees understand and apply consistently corporate cultural values, behavioral standards of VPBank
II. Requirements
1. Educational Qualifications
- Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or related field.
2. Relevant Knowledge/ Expertise
- 10+ years of experience in data science or advanced analytics, including at least 5 years in a leadership role.
- Proven track record of building and deploying machine learning and AI models in large-scale production environments.
- Expertise in statistical modeling, machine learning, deep learning, natural language processing, and big data technologies.
3. Skills and Competencies
- Proficiency in programming languages (Python, R, SQL) and experience with distributed computing (Spark, Hadoop) and cloud platforms (AWS, GCP, Azure).
- Strong leadership, stakeholder management, and communication skills, with the ability to influence at the executive level.
