Led cloud infrastructure and Site Reliability Engineering (SRE) teams, specializing in cloud optimization, automation, and monitoring for high system uptime and operational efficiency.Key Responsibilities:(a) Spearheaded the design and implementation of robust, scalable, and secure infrastructure for Huawei's payment system, ensuring seamless transaction processing and compliance with financial industry regulations.(b) Architected and managed high-availability systems in the banking and fintech industry, leveraging Huawei and AWS to maintain 99.99% uptime for critical financial services applications(c) Lead cloud infrastructure and SRE teams, maintaining and optimizing critical cloud environments across Huawei, AWS, and Azure(d) Managed deployment automation pipelines using Terraform, Ansible, and Jenkins, improving deployment efficiency by 40%.(e) Implemented microservices architecture using Node.js, Express, and MongoDB, resulting in scalable, high-performance applications with minimal downtime.(f) Integrated Docker and Kubernetes for containerization and orchestration, ensuring seamless application scaling and reducing downtime to less than 1%.(g) Deployed monitoring tools like Grafana and Prometheus to ensure high system uptime and rapid incident detection, reducing incident response time by 30%.(h) Provided leadership in Project Management, coordinating across multiple teams, defining project scopes, managing timelines, and ensuring resource allocation, all while aligning with business objectives.Trained and mentored junior engineers, promoting the adoption of Site(i) Reliability Engineering (SRE) best practices and improving team performance. Skills:(a) Cloud Optimization (AWS, Azure, Google Cloud)(b) Automation (Terraform, Ansible, Jenkins)(c) Containerization (Docker, Kubernetes)(d) System Monitoring (Grafana, Prometheus)(e) Team Leadership & SRE Best Practices

Led a team of developers, driving the design and development of scalable web and mobile applications, improving user engagement and operational efficiency.Key Responsibilities:(a) Directed a team of 10 developers in building and maintaining web and mobile applications using Node.js, Express, MongoDB, React, and Next.js.(b) Developed embedded software using C and C++ for real-time communication between vending machine hardware components (such as sensors and actuators) and the cloud-based management system, ensuring seamless operation and hardware control.(c) Utilized Java to build a secure and scalable backend for managing realtime data, inventory, and user transactions, ensuring smooth integration with the vending machine’s payment systems.(d) Implemented Java-based APIs to facilitate communication between the payment gateway and the vending machine’s software, allowing for secure processing of cashless transactions, including credit/debit cards, mobile payments, and e-wallets.(e) Integrated IoT technologies with the vending machine system, enabling real-time tracking of inventory and machine status, significantly improving operational efficiency and reducing downtime.(f) Led the integration of hardware-software communication protocols using C++, ensuring efficient data exchange between the machine’s internal components and external systems, optimizing product dispensing accuracy by 30%.(g) Designed the architecture for the payment system integration, ensuring compliance with industry security standards and enabling cashless payments through various methods, contributing to a 40% increase in cashless transactions.(h) Utilized React, Redux, and Next.js on the front end for dynamic and responsive web experiences.Skills:(a) Full Stack Development (Node.js, React, MongoDB)(b) Microservices Architecture(c) DevOps (Jenkins, GitLab CI, Docker)

Delivered user-friendly and responsive web interfaces at TDCX, enhancing digital customer experiences and improving website performance.Key Responsibilities:(a) Developed single-page applications (SPAs) using React.js and Angular, improving user experience and reducing load times by 30%.(b) Integrated Google Ads and Google Analytics to track user behavior, providing valuable insights to improve site monetization.(c) Optimized website performance using Lighthouse audits, resulting in a 40% increase in SEO rankings and faster load times.(d) Collaborated with backend developers to integrate RESTful APIs and enhance data-fetching processes.Skills:(a) Front-End Development (React.js, Angular, JavaScript)(b) Web Performance Optimization(c) Google Analytics & SEO(d) Responsive Design(e) API Integration

Research Assistant at the University of Nottingham Malaysia, specializing in data analysis, statistical modeling, and machine learning for academic research projects.Key Responsibilities:(a) Conducted advanced data analysis for various academic research projects using C, C++, Java, Python and R, including statistical modeling and machine learning.(b) Developed and deployed machine learning models utilizing libraries such as, Scikit-learn, TensorFlow, Keras, and PyTorch to support complex research in AI-driven predictive analytics and classification tasks.(c) Implemented deep learning algorithms, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), to process and analyze large datasets for image and text recognition projects.(d) Engaged in research involving large language models (LLMs) and natural language processing (NLP), optimizing model performance for tasks such as sentiment analysis and text summarization.(e) Leveraged the university’s high-performance computing cluster to run large-scale simulations and data processing tasks.(f) Gained in-depth experience with cloud platforms like Microsoft Azure and AWS to handle data storage, computation, and remote collaboration for research projects.(g) Collaborated with cross-disciplinary teams to apply AI and machine learning methods in cutting-edge research, contributing to multiple peer reviewed publications and academic conferences.(i) Automated data processing workflows using Python scripts, reducing manual intervention and improving the overall research process productivity by 40%(j) Assisted in writing research papers and presenting findings at academic conferences.Skills:(a) Data Analysis & Machine Learning (Python, R)(b) Cloud Platforms (AWS, Microsoft Azure)(c) Statistical Modeling & Simulations(d) Research Writing & Presentation(e) Workflow Automation