
I am an experienced and highly creative senior software engineer with 10+ years of experience. I am proficient in a variety of technologies, including but not limited to Java, .NET, C#, PHP, JavaScript, Node.js, Python, TypeScript, Commercetools(7years+), Spring MVC, React, Angular, Vue, Laravel, CodeIgniter, Entity Framework, RabbitMQ, HTML5 & CSS3, Redis, PostgreSQL, Oracle, Kafka, Apache Flink, and MongoDB. I am also proficient in working with Linux servers, cybersecurity tools, and Cisco network devices. I have a proven track record of delivering quality service and successful project outcomes. I am confident in my ability to develop, test, deploy, and maintain the latest technology.
I have deep financial solutions, fintech, banking solutions, payment gateway, loan solutions, blockchain technology solution, cryptocurrency, and payment integration experience, having spent 7years of my total working experience building solutions in the aforementioned industries.
In addition to my Software development skills and experience:
I have experience with a variety of:
Software development methodologies, including Agile and Scrum.
Cloud computing platforms include Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP).
DevOps tools, including Git, Jenkins, and Bash scripting.
I am confident that I can make a significant contribution to your organization. I am a hard worker, and I am always willing to go the extra mile. I am also a team player and always willing to help others. I have worked as an independent and collaborative team player. I am excited to bring my skills to your organization and contribute to your success.
Let's work together!




I take on a challenging research role in leveraging Machine Learning to Enhance Big Data Usage. * Algorithm Development: Design, imple...
I take on a challenging research role in leveraging Machine Learning to Enhance Big Data Usage. * Algorithm Development: Design, implement, and optimize AI/ML algorithms for various research projects. * Data Analysis: Collect, preprocess, and analyze large datasets to extract meaningful insights. * Model Training: Train and fine-tune machine learning models using state-of-the-art techniques. * Experimentation: Conduct experiments to validate hypotheses and improve model performance. * Collaboration: Work closely with faculty, researchers, and other team members on interdisciplinary projects. * Course Support: Assist in the preparation and delivery of lectures, labs, and workshops on AI/ML topics. * Student Mentorship: Provide guidance and support to students working on AI/ML projects. * Grading: Evaluate assignments, exams, and projects, providing constructive feedback to students. * Assist students with course-related questions and problems.