Software & AI Engineer from Málaga, Spain 🇪🇸 and I am a Specialist in implementing AI and Generative AI pipelines tailored to business needs.
Implement AI and Generative AI solutions across internal TuplOS tools and enterprise services to streamline workflows, enhance productivity, and unlock new capabilities at scale. My work focuses on integrating large language models (LLMs), retrieval-augmented generation (RAG), AI agents and automation into core business platforms—driving efficiency and intelligence across the organization.
This includes building custom AI pipelines, embedding models into internal APIs and UIs, and collaborating closely with cross-functional teams to identify high-impact use cases. The solutions I develop are production-ready, secure, and tailored to real business needs—empowering teams with smarter, AI-enhanced tools.
Designed and implemented a GenAI-based assistant to integrate automated monitoring and alerting functionalities into solutions built with the TuplOS platform. This involved analyzing functional and technical requirements to ensure seamless integration and configuring generative AI models to enable real-time event detection and proactive notifications. Additionally, I developed connectors and automated workflows to integrate the assistant with existing TuplOS solutions.
To enhance performance and user experience, I conducted functionality and usability testing, making optimizations based on feedback. Furthermore, I created technical documentation, user manuals, and tutorials to facilitate adoption and effective use of the assistant.
Developed business process optimization solutions using machine learning (ML) and Graph Neural Networks (GNNs). Worked with Business Process Model and Notation (BPMN) tools such as Activiti, Bonita BPM, and Camunda.
Applied my knowledge of artificial intelligence, focusing on machine learning and GNNs, while also utilizing genetic algorithms, neural networks, and optimization techniques.
Coauthored and published the SAES Python library for non-parametric statistical tests with researcher Antonio J. Nebro, enabling advanced statistical analysis and visualization.
Conducted research on automatic code generation using Large Language Models (LLMs), integrating LangChain with frameworks such as jMetal and jMetalPy for multi-objective optimization.
My name is Rodrigo, and I am a Software Engineer with professional experience in the design, development, and deployment of cutting-edge AI solutions. My primary focus lies in the practical implementation of Generative AI pipelines, especially within real-world business environments such as Kubernetes clusters and internal enterprise tools.
I have hands-on experience applying machine learning and natural language processing models to solve real challenges, particularly in computer vision and LLM-based systems. My work includes designing scalable MLOps architectures, optimizing model performance, and integrating AI into production-grade platforms. I hold multiple technical certifications from Nvidia’s Deep Learning Institute, and I have a solid foundation in GPU programming and parallel computation using CUDA.
I actively participate in major tech conferences such as Talent Land (where I spoke alongside a university professor), ARITH 2024 (as part of the organizing staff), DES 2024, YOLO Vision 2024, and various AI and cybersecurity events in Málaga. These experiences fuel my drive to stay at the forefront of technological innovation.
Outside of tech, I’m passionate about tennis and enjoy staying active. I also love creating and editing visually engaging content. I thrive in team environments, value building strong personal and professional relationships, and bring a self-taught, empathetic, and goal-driven mindset to everything I do.
