As a Software Engineer at Logifuture, I focus on backend development for gambling applications, particularly in the sports betting space. My role involves using modern technologies to build efficient and scalable systems that can handle high traffic and real-time data processing.- Backend Development: I work extensively with Python, utilizing Flask and FastAPI to develop robust backend services that power sports betting platforms. My focus is on ensuring scalability and efficiency, optimizing systems to handle the demands of real-time applications.- Unit Testing & Code Quality: A key part of my responsibilities is writing comprehensive unit tests to ensure the reliability of the codebase. This proactive approach minimizes issues in production and improves overall application performance.- Google Cloud Services: I work with Google Cloud technologies, specifically Datastore for data management and BigQuery for large-scale data analysis. These tools allow us to process vast amounts of data efficiently, which is crucial for sports betting operations.- Kubernetes Integration: While not directly responsible for managing cloud infrastructure, I collaborate with Kubernetes to manage and deploy microservices, ensuring smooth and scalable production environments.- CI/CD Pipelines: I maintain and improve Continuous Integration/Continuous Deployment (CI/CD) pipelines, automating the build, test, and deployment processes to streamline releases and maintain code consistency.This role has strengthened my expertise in backend development, cloud technologies, and automated workflows, enhancing my ability to deliver high-performance solutions.

Technologies frequently utilized: Go, MongoDB, Redis, Docker, Python, FastAPI, PostgreSQL, Solidity.- Developed a Telegram game and DEX swap, managing the backend in Go, and integrating MongoDB and Redis.- Implemented basic JavaScript game logic and contributed to Docker deployment and CI/CD pipeline creation alongside the DevOps team.- Designed and developed the entire backend for a Key Opinion Leaders (KOL) platform using Python with FastAPI and PostgreSQL.- Explored Solidity and smart contracts to enhance the platform's functionality.

In my role as a Software Engineer at QCerris, I was actively involved in backend development for logistics and transportation platforms, leveraging various technologies to drive system improvements. My contributions were as follows:- Technological Expertise: Utilized a range of technologies including Python, Django, FastAPI, pytest, Docker, Git, SQL, Redis, Kafka, and Jenkins. My application of these tools contributed significantly to the development and scaling of advanced logistics platforms.- Logistics Platform Development: Participated in building and architecting three logistics platforms, contributing to the development of their core logic and planning for future enhancements.- System Integration: Assisted in integrating the platforms with Kafka, Redis, and McLeod, enhancing the efficiency of data transfer in the supply chain.- Lead Backend Technologist - EDI Project: As the Lead Backend Technologist for the EDI project, I not only developed a Python library and multiple EDI templates but also took on a leadership role. I guided and mentored interns, demonstrating my capabilities in leadership while implementing innovative solutions to ensure the reliability of these templates.- API Integration and Cloud Infrastructure: Helped integrate the platforms with McLeod's API using webhooks and cron jobs. Also proficiently managed cloud-based infrastructure, including the deployment and configuration of AWS S3 buckets.My experience at QCerris enriched my software engineering skills, particularly in the logistics and transportation sector, embraced leadership opportunities, and underscored the importance of collaborative development in achieving technical excellence.

At BlueGrid, my experience spanned across various technical and support aspects:- API Support and Integration: In my initial role, I assisted merchants with integrating the ReCharge API, offering effective solutions and workarounds. This involved understanding their needs and ensuring they could leverage the full potential of the API for efficient goal achievement.- Backend Development and Troubleshooting: As a Software Engineer, I focused on resolving backend issues within the Flask framework, primarily in pre-production and pre-stage environments. This role required a detailed understanding of backend systems and quick problem-solving skills.- Data Analysis and Log Management: I frequently used SQL queries, Splunk, and Looker to search and analyze logs in the database. This process was crucial for diagnosing and addressing issues effectively.- Payment Processor Implementation: A significant part of my role involved working on payment-related issues and integrating various payment processors, including Shopify Payments, Stripe, Braintree, and Authorize.Net. This experience enhanced my understanding of e-commerce payment systems and their technical integrations.This period was marked by significant professional growth, as I transitioned from providing API support to taking on more complex software engineering challenges, thereby expanding my technical skill set in the industry.

At Kortechs, I contributed to the backend development of a transportation-focused application, gaining valuable experience in various aspects of software development. My key learning experiences included:- Django Framework: This position provided me the opportunity to learn and apply the Django framework, enhancing my skills in building and maintaining efficient backend structures.- RESTful API Development: I was involved in the development of RESTful APIs, a process that significantly improved my understanding of server-client interactions and backend to frontend communication.- Database Management: Working with PostgreSQL databases, I learned about effective data management, focusing on how to optimize data storage and retrieval for better application performance.- Technology Integration: I was introduced to using Docker for containerization, which was vital in understanding deployment processes. Additionally, I learned the essentials of version control with Git, which was crucial for team collaboration and code management.This early career experience was instrumental in developing my foundational skills in Python programming and backend development, setting the stage for my future growth in the field.

During my internship at VLATACOM Institute, I was engaged in an innovative project focused on developing and training a Generative Adversarial Network (GAN). My primary responsibilities included:- Dataset Development: I spearheaded the creation of a specialized drone image dataset, which involved extensive research and data curation. This dataset was crucial for training the GAN model.- Model Enhancement: Leveraging a pre-trained GAN, I worked on modifying and fine-tuning the model to generate new, high-quality drone images. This task required a deep understanding of GAN technologies and creative problem-solving skills.This experience allowed me to deepen my expertise in machine learning, particularly in the area of generative models and contributed significantly to the project's goal of creating new drone imagery through advanced AI techniques.