Jazmin Barrionuevo
Jazmin Barrionuevo
I'm a software developer dedicated to create innovative solutions with careful design, efficient programming, and seamless deployment.
I train AI models using Reinforcement Learning with Human Feedback (RLHF). My role involves not just fixing code but also evaluating and arguing why certain inputs improve model performance, ensuring that AI systems make more accurate decisions based on user interactions.
In collaboration with a colleague, I developed a comprehensive digital menu and restaurant management system for a client, including a website and an administrative app. We implemented best practices such as a clean infrastructure using RESTful APIs, microservices, and containerization with Docker. Our tech stack included TypeScript, Next.js, SQL, AWS, and NestJS. We established a CI/CD pipeline with automated testing and secure coding standards. Adopting an agile approach, we ensured iterative development and continuous client feedback. Our focus on UX/UI provided an intuitive and engaging experience for both customers and administrators, enhancing the restaurant's operations and overall user satisfaction.
As a Genexus Analyst, I am actively engaged in both small-scale projects from their inception and ongoing projects. My responsibilities encompass the analysis of business requirements, translating them into functional specifications, and collaborating with stakeholders to align applications with business needs. Beyond Genexus development, I am involved in continuous research as I am in the Development and Research sector. This dual role allows me to not only contribute to the immediate project needs but also stay abreast of emerging trends and technologies that could enhance our development processes. In the DevOps realm, I specialize in Jenkins and utilize MsBuild code to streamline and automate the software delivery pipeline. My focus is on creating efficient CI/CD processes for Genexus applications, ensuring smooth collaboration between development and operations teams. This includes automating testing processes and optimizing application performance in production.