Role Overview:
Provides technical and strategic leadership for the organization’s AI platform and practices. This role defines the AI operating model, guides platform architecture, and ensures the scalable, secure, and production-ready delivery of AI systems aligned with business objectives.Acts as a bridge between business stakeholders, AI engineering, infrastructure, and data teams, enabling enterprise-wide AI adoption while ensuring strong governance, reliability, and value realization.
Responsibilities:
- Define the enterprise AI vision and roadmap aligned with long-term business priorities and technology strategy.
- Identify and prioritize high-impact AI use cases, focusing on agentic workflows, predictive analytics, and personalization.
- Establish architectural standards and technical guidelines for scalable, high-performance AI platforms and solutions.
- Advocate for and drive AI adoption across all organizational departments and business units.
- Report progress and key performance metrics to executive management to ensure transparency on AI ROI and milestones.
- Facilitate cross-functional collaboration between product, engineering, and business leaders to align technical output with user needs.
- Oversee the architecture and management of private GPU clusters to ensure high availability for model training and inference.
- Define the long-term hardware roadmap and procurement strategy to balance compute power with organizational growth.
- Set and enforce rigorous standards for coding, deployment, research, and engineering excellence.
- Own the AI intake and assessment process to ensure initiatives meet commercial viability and strategic fit.
- Oversee the development of production-ready pipelines to ensure seamless transition from R&D to deployment.
- Ensure AI systems are architected for maximum security, maintainability, and global scalability.
- Maintain a competitive edge by tracking AI advancements and evaluating emerging tools and frameworks.
- Implement responsible AI governance, focusing on transparency, explainability, auditability, and regulatory compliance.
- Manage the balance between rapid innovation and AI safety protocols to protect the brand and its users.
- Lead and scale multidisciplinary teams across engineering, data, design, and product to ensure operational maturity.
- Maintain a consistent physical presence across different offices, traveling between Ipoh and PJ to provide on-site leadership and team alignment.
- Perform any ad-hoc tasks which may be assigned from time to time
Qualifications & Skills:
Education:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related fields.
Experience:
- Proven leadership in managing technical teams
- Proven experience delivering AI or machine learning systems at enterprise scale, from concept to production.
- Demonstrated background in AI platform, MLOps, or large-scale AI system architecture.
- Experience in a technical leadership, principal, or lead engineering role with cross-functional responsibility.
- Strong exposure to Agile or iterative delivery environments.
Technical Expertise:
- Deep understanding of AI and machine learning concepts, including Generative AI and modern AI architectures.
- Hands-on experience with AI model lifecycle management, including training, deployment, monitoring, and optimization.
- Solid experience with containerized AI workloads using Docker and Kubernetes.
- Familiarity with MLOps practices such as CI/CD for AI, model versioning, and observability.
- Experience with major cloud or hybrid platforms is an advantage.
Certifications:
- CKA or CKAD certification is a strong advantage.
- NVIDIA Professional / Deep Learning Institute (DLI) certification is an added advantage
Applicants must be willing to work in both Petaling Jaya, Selangor and Ipoh, Perak.
Benefits:
- KPI rewards
- Employee Shares Option Scheme (ESOS)
- EPF, SOCSO &EIS
- Overtime Claim
- Annual Leave/ Medical Leave/ Wedding Leave, etc
- Medical Claim
- Staff Purchase Scheme
- Product Training: Apple/ Intel/ Microsoft, etc
- Oversea Trip: Asia, America, Australia, Europe
- Salary Review- Twice per year
Benefits:
- Opportunities for promotion
- Parental leave
- Professional development
Education:
Experience:
- Machine Learning: 1 year (Preferred)
- Artificial Intelligence: 1 year (Preferred)
Language:
- English (Preferred)
- Bahasa Malaysia (Preferred)
- Mandarin (Preferred)
Location:
Willingness to travel:
Work Location: In person