Introducing our speakers, the Voices behind the talks ✨

Alfonso Palacio is a Systems Engineering student at Politécnico Grancolombiano with a strong focus on applied artificial intelligence. He has worked on projects involving machine learning, computer vision, and data analytics, including BachAI, a YOLOv8-based system for automatic pothole detection. He has experience with Python, data processing, and cloud-based solutions, and has contributed to initiatives such as Microsoft Learn Student Ambassadors and collaborative tech projects. Alfonso is passionate about building AI solutions that solve real-world problems and about sharing practical knowledge to help others leverage these technologies in their own work.

I'm Ana María López Moreno, passionate about data, artificial intelligence, education, and tech communities. I currently work as Senior Partner Solution Architect in Data & AI at Microsoft, where I support partners and organizations in adopting data, analytics, and artificial intelligence solutions. I'm also a university instructor and coordinator of the Software and Data Engineering program at Institución Universitaria Digital de Antioquia, a role that lets me connect industry with academia and guide new generations of technology professionals. My experience has focused on data platforms, generative artificial intelligence, MLOps, cloud architecture, and building applied solutions with real impact. I've been a speaker at PyCon Colombia 2023 and 2024, and in 2025 I had the opportunity to speak at KubeCon, sharing experiences around technology, data, artificial intelligence, and technical communities. I'm interested in building knowledge in a close, practical, and useful way. I enjoy sharing learnings, creating spaces for conversation, and motivating more people —especially students and growing professionals— to explore the potential of Python, data, and artificial intelligence to solve real problems. For me, being part of communities like PyCon Colombia means learning, contributing, and continuing to build technology from Latin America for the world.

Economist, Machine learning engineer with +8 years of experience building ML/AI systems in production. Currently at Globant, I work on designing scalable and secure AI applications and use cases in critical processes such as industrial processes and security.

He is a master's student in applied mathematics and a research assistant, with experience in natural language processing (NLP), integration of heterogeneous databases, and data analysis. He currently works on using the Bayesian g-formula as a solution to the multiplicity of causal effect estimators and on using machine learning models to estimate pollutant gas emissions and fuel consumption for low-displacement motorcycles in the Colombian context. As a research assistant and scholarship holder on the Comparative Analysis of Perceptions on Protective Behaviors against COVID-19 in Colombia project, he has worked on teams made up of students and researchers from diverse disciplines to study how public discourse circulates on social networks and how it behaved regarding care habits during the pandemic. At PyCon Colombia 2026 he will participate as moderator of a workshop on natural language processing for corpus analysis in Digital Humanities, sharing experiences on how Python can become a meeting tool between technology and the humanities.

Andrés is an applied AI engineer and researcher with a background in Artificial Intelligence, Bioinformatics, and Biotechnology. His early work in computational biology and machine learning grew into a broader focus on using AI to tackle complex, real-world problems across industries. As a startup co‑founder, he developed a strong, problem‑solving mindset, focused on shipping solutions that create tangible impact rather than just prototypes. Over the past years he has led the design and deployment of production-grade systems, including large-scale video and audio analysis pipelines, intelligent virtual assistants serving tens of thousands of users, and document automation platforms that reduced operational costs by more than 90%. His leadership in AI innovation has been recognized by the U.S. Department of State, which named him one of the Young Leaders of the Americas, and by the Royal Academy of Engineering in the United Kingdom for his contributions at the intersection of AI and innovation. Based in Medellín, Colombia, he divides his time between building AI products, mentoring others, and sharing his experience through talks and workshops on applied AI.

I have been in artificial intelligence for a good while — I started on the ML and data science side, and evolved until landing where excites me most today: GenAI and conversational agents. Now I lead a team where we build real things with language models, not just lab experiments. I move comfortably between theory and "okay, but how do we actually make this work?" I design agent architectures, work with LLMs, and think hard about how generative AI can solve concrete problems. If you are here it is because you are curious too — so we are on the same wavelength.

Biviana Marcela Suárez Sierra is a statistician and data science researcher, with experience in statistical modeling, machine learning, and computational analysis of complex data. She is currently a university professor and leads interdisciplinary research projects that integrate statistics, programming, and data analysis to address problems in health, energy, the environment, and digital humanities. Her recent work has focused on developing methodologies for analyzing large textual corpora through natural language processing (NLP) techniques, text mining, and statistical learning. As a linked researcher on the project Art, science and technology in the public sphere: the contribution of Digital Humanities to the analysis of discourses in the public sphere in Colombia, she has led teams made up of students and researchers from diverse disciplines to study how discourses about science, culture, and society circulate in Colombian media. She has more than a decade of experience in research and data analysis, both in the academic sector and in public and private entities. Her main interest is building bridges between computational tools and real problems, promoting collaboration spaces among data scientists, programmers, linguists, health professionals, and social science specialists. At PyCon Colombia 2026 she will participate as director and moderator of a workshop on natural language processing for corpus analysis in Digital Humanities, sharing experiences on how Python can become a meeting tool between technology and the humanities.

I'm Brayan Echenique, AI Software Engineer at Protección, where I design and implement artificial intelligence solutions integrating emerging technologies with robust architectures. I'm an advocate of technical pragmatism and firmly believe the best solution isn't always the most complex, but the one that solves the right problem with the right tools.

I am a Systems Engineer from Universidad Distrital and an Electronics Engineer from Universidad Nacional de Colombia. I currently work as a Senior Software Engineer at Epam, I have a master's degree in Software Engineering from Universidad de los Andes, and I tutor some courses there. I have worked for almost 10 years in the software development world for national and foreign companies in different verticals, in IC and TL roles with Python. I have two children. I love learning, traveling, and spending time with my family.

Mathematician (Summa Cum Laude) and MSc in mathematics. Machine Learning Engineer and Data Scientist with 6+ years of experience delivering Data Science and AI solutions across industries like retail, finance, education, and social enterprises. Skilled in developing and deploying advanced models for tasks such as recommendation systems, customer clustering, churn prediction, transactional risk, LLM-powered chatbots, Gen-AI applications and search engines using tools like Python, PyTorch, PySpark, FastAPI, PydanticAI, Qdrant, LangChain and cloud platforms (AWS, GCP and Azure). Passionate about leveraging math and AI to drive meaningful change.

I'm a high-performance machine learning athlete. I practice speed skating, where Colombia is a world power. I apply the same mindset and effort to machine learning, striving to be the best and build incredible things along the way. I've been involved in technology development for 10 years, 5 of them in machine learning, and I still want to continue impacting the world with what I build.

I'm Christian Urcuqui, Cybersecurity Data Scientist with over 11 years of experience in artificial intelligence, cybersecurity, and production machine learning systems. I've worked on designing and evaluating AI systems for threat detection, behavior analysis, and agent-based architectures. I currently collaborate with international organizations on AI Security content and solutions, including agent pentesting and threat modeling. I've been a speaker at events like DEF CON, Ekoparty, BSides, and PyCon, and I'm the author of books on artificial intelligence applied to cybersecurity. My approach combines research, offensive practice (adversarial ML), and secure system design.

I'm a Full Stack developer passionate about creating elegant, functional digital solutions. My focus is on writing clean, maintainable, and scalable code that not only works but also delivers an excellent user experience. I mainly work with modern technologies that have allowed me to build robust, high-performance applications for startups in the United States and Ecuador. Beyond development, I enjoy continuous learning, sharing knowledge in tech communities, and contributing to open source projects whenever possible.

Machine Learning Engineer and Data Engineer with a background in Astronomy and Astrophysics and over 5 years of experience designing, building, and deploying scalable data pipelines, ML systems, and Big Data solutions on AWS and Databricks. My academic training in physics and computational astrophysics—including large-scale cosmological simulations, statistical inference on observational data, and numerical methods—provides a strong analytical foundation for solving complex data and ML problems. I specialize in building end-to-end machine learning pipelines, RAG systems, and agentic AI workflows, as well as optimizing big data processes using Apache Spark, SQL/NoSQL data modeling, and cloud-native architectures.

I have won 3 times the best project award in Systems Engineering at EAFIT. I have given talks at Medellín JS, Python Medellín twice, Medellín AI, PyCon Colombia, Python Moscow, and BarNLP. I am half Colombian, I also have German and Russian heritage, and I speak Russian and German.

Daniel brings over five years of experience in consulting, optimization, data visualization, and data pipelines. He is passionate about all data fields, and his experience allows him to understand needs across Data Science, Data Engineering, and Data Analysis.

Daniel is a biologist by training and works at the intersection of life sciences, data, and software. He builds ML systems alongside internationally distributed multidisciplinary teams, spanning cloud infrastructure and bioinformatics research. He is especially interested in how AI tools are transforming the way developers actually work and what it means to stay effective as those tools, and the abstractions behind them, continue to evolve.

CEO of Gudar Devs SAS and software engineer with more than 10 years of technical experience. I lead teams specialized in developing scalable web applications, where I prioritize robustness and operational efficiency. In addition to my work at Gudar Devs, I am a university instructor and the current leader of Python Barranquilla, a community I have belonged to since 2016.

I'm an economist and MSc in Data Science; much of my story unfolds in the electric sector where I've grown in automation, data management, and leadership of initiatives. However, beyond the workplace, I'm always accompanied by a passion for research and social issues—one of them food security and nutrition, a topic that accompanied me throughout university and also marked my postgraduate life. Sometimes food issues are underestimated, but the truth is they shape poverty traps, fiscal pressure, and limitations that can mark people for life. I think we're in a privileged time when previously invisible problems can gain observability through creativity using public data and Python.

Machine Learning Scientist and Cloud Infrastructure Architect. With a career spanning from information security to DevOps, I'm a Google Developer Expert in ML and Docker Captain. Passionate about multiplying matrices at high speed, I currently work as an AI Engineer at Dataiku.

David is a data engineer at Loka, a technology consulting firm, where he designs and maintains data platforms on AWS for clients across multiple industries. With nearly five years of experience in the field, his day-to-day work revolves around Apache Iceberg, PySpark, Airflow, and production lakehouse architectures, not in tutorials, but in real systems with real incidents. I hold three AWS certifications, including Solutions Architect Associate and a Databricks certification, reflecting both my command of cloud infrastructure and my hands-on experience with distributed data processing. I have led projects ranging from ClickHouse replication pipelines to Iceberg table maintenance jobs running on Kubernetes, and have recently explored the intersection of data engineering and AI agents, building personal tooling on top of the Anthropic SDK. Based in Bogotá, I believe there is a shortage of practical Spanish-language technical content on modern data engineering, and that PyCon Colombia is exactly the right place to start closing that gap.

I am a DevOps/Cloud Engineer with more than 8 years of experience in Tech. I currently participate in AI projects where I have been able to go deeper into GenAI without limiting my scope only to infrastructure or DevOps. I have been a speaker at multiple events and I lead 2 communities: CloudCrafters and AI AWS UG Colombia.

Dora Cecilia Alzate, a student in the Master's in Humanistic Studies, linked to the language area and the School of Arts and Humanities, would share the main challenges and linguistic decisions that made it possible to adapt these tools to Spanish and improve the quality of results obtained in text processing.

Engineering Manager & Data engineer with strong experience in architecting, developing, and maintaining highly reliable analytical data infrastructure and data pipelines that move data in and out to enable better decision-making and create business value primarily within the Fintech sector. Proficient in AWS, Google Cloud, Snowflake’s data ecosystem, Airflow, dbt, and other tools. Cares about other team members and is invested in empowering them to grow personally and professionally. Works cross-functionally with stakeholders (software engineers, data scientists, business analysts, etc), to ensure that the data infrastructure meets their evolving needs. Currently, working as a Data Engineering Manager at Factored (one of the fastest-growing data science companies in the Americas, we build very high-caliber teams of rigorously vetted data scientists for top US companies).

Elbano is a Senior DevOps Solutions Architect at Provectus, an AWS Premier Consulting Partner and official Anthropic partner, with over 9 years of experience in cloud-native, AI, DevOps, and distributed systems design. He holds two AWS certifications, three AWS Black Belt specializations, and an ITIL Foundation credential. His career started in telecommunications engineering in Venezuela, moved through fintech integrations, full-stack development, and IT management in Colombia, and eventually converged on cloud architecture and AI. Before joining Provectus, he led a team of 17 solutions architects across 5 regional teams in LATAM and spearheaded a Generative AI practice that achieved AWS Generative AI Competency. Today, he works at the intersection of cloud infrastructure, agentic AI, and enterprise delivery, designing solutions that range from multi-account AWS platforms for AI agent orchestration to intelligent contact centers with Amazon Connect and Bedrock. The frustration of watching AI coding agents ignore architectural decisions and produce code that "sort of works" in real enterprise engagements is what drives this talk. As a daily Claude Code user, Elbano has experienced firsthand both the power and the limits of AI-assisted development, and believes the most valuable skill for the next generation of developers will not be writing code, but communicating intent with enough precision that an agent gets it right the first time.

Passionate about artificial intelligence, software development, and the ever-evolving world of emerging technologies, I have over three years of experience in the Data, Machine Learning, and MLOps industry. My curiosity drives me to continuously learn and explore the latest advancements in AI, cloud computing, and automation. Currently, I am deepening my expertise in MLOps, researching and implementing best practices to streamline the deployment and scaling of machine learning models. I have hands-on experience working with AWS and GCP, leveraging cloud technologies to build scalable and efficient AI-driven solutions.

Physics Engineer and Machine Learning Engineer passionate about the social impact of technology. My trajectory in the data world has been a comprehensive journey: from data analysis and engineering to data science and specialization in MLOps, which allows me to understand the lifecycle of a model from all its angles. I am currently finishing my Master's in Analytics, combining academic rigor with the implementation of scalable solutions in industry. I firmly believe that data and innovation are engines for sustainable development. When I am not optimizing pipelines in Databricks or exploring new AI/ML architectures, you will find me on a field tennis court or enjoying a good television series.

Software Engineer with more than 8 years of experience building scalable, high-impact technology platforms, especially in the fintech sector. I am passionate about creating efficient solutions, leading technical teams, and promoting an innovation culture focused on real results. I currently have an AI-First focus, integrating Artificial Intelligence into products and processes to optimize operations and accelerate companies' technological evolution. Throughout my career I have worked on software architecture, platform scalability, process automation, and technical leadership of multidisciplinary teams. I want people to know me for my ability to transform complex ideas into scalable, efficient, future-oriented technology solutions. I am passionate about combining engineering, innovation, and artificial intelligence to build products that generate real impact and help companies grow sustainably.

Felipe Sanchez is an Analytics Consultant and Claude Certified Architect with more than six years of experience designing data and analytics solutions for Fortune 100 organizations. His expertise spans analytics engineering, decision intelligence, agentic systems, and modern data platforms. Felipe specializes in translating complex business challenges into scalable technical solutions and is passionate about teaching practical AI engineering patterns that developers can apply in production. His work focuses on the intersection of Python, analytics, data systems, APIs, and agentic systems.

I’m Felix Miño, a senior software developer with over 7 years of experience building robust, scalable systems. I’m particularly interested in functional programming principles and advanced testing techniques to improve software reliability. I’ve worked with Python, Haskell, and Kotlin, exploring how functional concepts and testing strategies, like property-based testing, can lead to safer, more maintainable code. I’m especially interested in making these ideas practical and accessible for Python developers. Since 2022, I’ve led the Quito Lambda Meetup in Ecuador, where I help grow a Spanish-speaking community around functional programming and modern software practices.

I am Francisco Moya, Lead Analytics Consultant at Aimpoint Digital, where I design and build data and artificial intelligence solutions for companies that want to turn their information into real decisions and actions. Over my 5 years in the data world I have worked across the full analytics cycle: from modeling and transforming data to building dashboards and AI applications that people actually use in their daily work. I hold a Master's in Data Science and Analytics, am a Claude Certified Architect, and have the Sigma AI Apps certification, credentials that reflect something I am obsessed with: always being on the frontier of what AI makes possible. I am passionate, above all, about how artificial intelligence transforms processes and reinvents workspaces, and I enjoy taking those concepts from marketing to the keyboard so anyone can apply them. That vocation for teaching I also live in the classroom: I am a university instructor in AI and data processing topics. I firmly believe in learning by building, and that is exactly the experience I want to bring to this workshop. Outside the data world, I am a black belt in taekwondo and I love dancing.

Hi! My name is Gerardo and I'm a Mechatronics Engineer with a Master's in Embedded Artificial Intelligence. I currently work as Senior AI Engineer at the technology consultancy NTT DATA, leading generative AI projects where we apply text, audio, and image generation models in solutions for the banking and insurance sectors across Latin America. I also work as a research professor at Universidad de Buenos Aires, where I teach Deep Learning and Computer Vision courses. Additionally, I lead research projects at the Embedded Systems Laboratory focused on robotics and satellite systems. I have a 5-year track record as a speaker on engineering and artificial intelligence at international conferences, which has allowed me to share and learn with different communities at events held in more than 15 countries.

I'm a Colombian software engineer with 11+ years of professional experience, and entrepreneur working in Python, TypeScript and open source development. I currently work as an AI Engineer at Backblaze. Previously, I worked at Datalayer building tools at the intersection of Jupyter, AI, and collaborative computing, at Quansight contributing to the scientific Python ecosystem, and at Anaconda as Technical Lead for Anaconda Navigator. My career spans from water resources engineering (MSc from IHE Delft and Erasmus Mundus) to becoming a core contributor to major open source projects including Spyder IDE, JupyterLab, and napari, conda-forge among others. I've created over 400+ conda-forge recipes and led internationalization efforts for JupyterLab and automating efforts in the Scientific Python Translations project. I also co-founded Trepa, a climbing gym in Bogotá, Colombia, where I have developed tools to manage the business and community by automating workflows with AI. These include scraping workflows, chatbots, automatic review and messaging system, and Data Analysis, all to support the Business decissions. I'm deeply committed to the Latin American Python and open source communities. I co-founded PyCon Colombia, helped organize SciPy Latam, and serve on the Python Software Foundation Grants Working Group. I believe in making technology accessible across languages and borders, and I'm passionate about mentoring the next generation of developers in Latin America. I have been a hobby climber since 2021 and a musician, playing keyboards, guitar and choruses with a local band.

Hazel Saenz is a LATAM Developer Advocate at Amazon Web Services (AWS) and Former AWS Serverless Hero, with more than 20 years of experience in application development and 6 years working with cloud technologies. She specializes in serverless architectures, event-driven systems, and Generative AI on AWS, and actively participates as a speaker at AWS Summits, Community Days, and international conferences, sharing practical knowledge with the developer community in Latin America.

Isabel is an ML Engineer at Loka, a machine learning consulting firm, where she has worked on projects spanning multiple industries and clients. She enjoys the full arc of ML work, from experimentation to building tools that make it into the hands of real users. Curious and hands-on, she is especially interested in AI agents and how they are changing the way developers build and think about software.

I'm a student at Universidad Nacional with a strong interest in machine learning. I enjoy creating animations in Manim because they're really cool and let me teach how these systems work under the hood. My goal is to take concepts that often seem strange or abstract and show them visually and through animation so they become much clearer and more accessible.

Currently completing my undergraduate degree in Physics at Universidad de Antioquia, I have experience in signal processing, high-performance data acquisition systems, and development of solutions for scientific instrumentation. I have worked on the design and implementation of solutions based on reconfigurable hardware, Xilinx System on Chip (SoC) architectures, with data analysis capabilities in Python, modeling, integrations with embedded systems, and computer vision. Passionate about technology, I consider physics a transversal training that strengthens analysis, modeling, and the ability to address complex problems in different technological contexts.

I am a Technical Lead and Computer Engineer graduated from UNET, and I have spent 9 years building resilient software and empowered teams. I am deeply passionate about technology education; I currently mentor engineers at EPAM and also founded PyDojo there, a community focused on promoting regional Python talent within the company. Outside the screen, I share my home and daily life with my wife and our four cats. I also practice karate, search for asteroids as a citizen scientist for IASC, and find my artistic balance painting, playing classical piano, and practicing operatic singing.

Johnny Alexander Montoya Franco is an AI R&D Engineer at LaHaus, where he leads the GenAI and Voice AI strategy for Colombia's leading PropTech: an end-to-end real estate call platform with 2.5k+ conversations/month and sub-second latency, and LaHaus-Arena, a proprietary framework that evaluates 20+ LLM model families from 5 providers with over 98% completeness. Before LaHaus, he was Senior Data Engineering Lead at Nequi (Bancolombia), where he built from scratch the data infrastructure of Colombia's first digital bank until scaling it to 20M+ users and peaks of 1.5M+ operations/hour, including the real-time fraud detection pipeline. He has 14 years transforming industries with data and AI, has been a speaker at PyCon Colombia 2023 and 2024, was selected by Bancolombia for the Plug & Play Accelerator in Palo Alto (2018), regularly attends the AI Engineer World's Fair and The AI Conference in Silicon Valley, and is a long-time open source advocate at the Unloquer Hackerspace in Medellín (Airflow, dbt, Metabase, LangChain). He is currently building Centinela, a multi-tenant AI agent platform in production for clients in Colombia, and it is the technical foundation of this workshop.

I'm a physicist with a master's in theoretical physics and a second master's in Visual Analytics and Big Data, currently pursuing a specialization in statistics at Universidad Nacional de Colombia. I work as an analyst at the Procuraduría General de la Nación, applying machine learning, NLP, and geospatial analysis to preventive oversight and monitoring problems in the different axes from the Directorate of Strategic Support, Data Analysis and Information. My path runs from simulating superconductor systems to developing deforestation detection tools and electoral analysis, always with Python as the common thread. I'm passionate about bringing data science to spaces where it rarely arrives: Latin American public institutions.

I am passionate about software development, leadership, and personal growth. I deeply believe that every person, if they truly decide to, has the ability to actively build their life and reach great personal and professional goals. For me, everything begins with the ability to take action, have initiative, autonomy, and take control of the decisions that define our path. One of the principles that identifies me most is: "never stop learning." Learning constantly gives meaning to my life. I enjoy facing new challenges, stepping out of my comfort zone, and discovering new ways to grow both technically and as a person. I am also passionate about positively impacting the people around me. I like sharing my learnings, experiences, and mistakes, with the intention of contributing even a small grain of sand to others' growth. This is part of my daily life from my leadership role at LendingFront, where I seek to empower teams, mentor people, and build a culture of continuous learning, but I also apply it in my personal life with those I have the opportunity to share and grow with.

Hello, I am José Arturo Osorio, Senior Tech Lead at Lovelytics, where I lead the Data Science, MLOps, and Generative Artificial Intelligence team for Latin America. With more than 8 years of experience in the data science field, I have grown alongside the evolution of the industry, working across the full spectrum of machine learning and artificial intelligence technologies. My experience ranges from classical machine learning models, including classification and regression with tree-based algorithms, to statistical modeling such as time series analysis and survival models. I have also developed deep learning solutions for computer vision, especially in semantic segmentation and named entity recognition (NER). I have applied these technologies across diverse sectors, including banking, services, and healthcare, always with a direct focus on business needs and value generation for clients. From a technical perspective, I have designed and implemented cloud-native machine learning solutions using mainly Azure, AWS, and Databricks. I specialize in developing AI and machine learning systems that generate tangible business impact, with measurable results aligned with strategic objectives. I also hold a master's degree in areas related to analytics and artificial intelligence, as well as professional certifications in AWS, Databricks, and Microsoft Azure.

Jose is a Senior ML Engineer with experience building machine learning systems across multiple industries, from security applications, logistics optimization and healthcare. He works with internationally distributed, multidisciplinary teams on complex, fast-moving problems. Curious by nature, he is particularly interested in where AI tooling intersects with how developers actually work — and what the next generation of AI-assisted development will look like in practice.

I'm a solutions architect focused on systemic efficiency and building software designed for real-world challenges. My professional focus sits at the intersection of generative AI and cloud-native architectures, where the real challenge isn't just getting a model to respond, but doing so resiliently, scalably, and in a financially sensible way. Throughout my career I've led application modernization in hybrid cloud environments, facing the complexity of integrating cutting-edge services with critical infrastructure.

I am an AI and Software Consultant dedicated to transforming businesses through intelligent and scalable solutions. As a Google Developer Expert (GDE) in Firebase, GCP, Kotlin, and AI, I am recognized by Google for my exemplary work and deep technical knowledge. My professional focus lies at the intersection of Software Engineering and Artificial Intelligence. I provide expert consulting in Cloud Architecture and AI implementation, helping companies leverage Google technologies to solve real-world problems. Currently, I am expanding my research capabilities by pursuing a Master's degree in Artificial Intelligence and Data Sciences at Universidad Autónoma de Occidente, building upon my previous Master's in Software Engineering from Universidad de San Buenaventura Cali. I am passionate about sharing this expertise, regularly speaking at local and global events to empower developer communities worldwide.

Technical Lead and AI Architect with more than 3 years of experience designing and deploying artificial intelligence systems, software architectures, and production-ready automation ecosystems in enterprise environments. I specialize in connecting advanced Deep Learning and LLM theory with scalable real-world implementations, with a strong focus on reliability, maintainability, and measurable business impact. My experience includes leading AI initiatives on Azure, designing multi-agent and RAG-based systems, and guiding technical teams through software design patterns, best practices, and production-grade engineering standards. I have delivered solutions capable of reducing days of manual work to minutes, maintaining high levels of accuracy and operational robustness. In parallel, I lead research on Transformer optimization and LLM efficiency through mathematically rigorous, PhD-level work focused on improving the computational performance and internal mechanisms of these models. I am also passionate about AI outreach, technical mentoring, and translating complex systems into high-impact practical solutions.

He grew up learning English from software installation menus and YouTube tutorials before they existed in Spanish. That early curiosity about technology took him from Industrial Engineering and financial analysis at Javeriana to building data pipelines for companies in three countries. Juan Manuel is a Senior Data Engineer with experience in GCP, Python, and automation, and has worked from B2B trade platforms with Asia to BI projects at Cisco. At Attento he handled what he likes most: keeping data flowing cleanly, making infrastructure invisible, and making the system remember what you did yesterday.

Industrial Engineer turned Data Scientist out of love for numbers and technology. Juliana went from modeling probabilities at Javeriana to fraud detection models at MercadoLibre and MercadoPago, and today builds AI solutions at Cuesta Partners, a Tech and AI consultancy. Attento is her latest experiment: proving that Python can connect a human voice with ten corporate APIs without losing your mind along the way. Off the keyboard, she just graduated as a Chef, where she applies the same technical rigor as in her professional life.

Karen Melissa Gomez Montoya is a mathematical engineer and master's student in Data Science and Analytics at EAFIT, where she also works as a research assistant on digital humanities and public sphere projects. Her work sits at the intersection between computational methods and textual corpus analysis.

I'm a software engineer who loves learning new stuff and working on exciting projects. I enjoy working on

I'm a data scientist and engineer based in Medellín. I started my career in Mechatronic Engineering and somewhere along the way fell in love with data, which led me to a Master's in Data Science & Analytics. Since then I've worked remotely across LATAM and the US at companies like Holafly, Lemontech, and the ICIPC. I have built data pipelines, machine learning models, dashboards, ETL processes, backend development, and analytics tools to help teams make better data-driven decisions. These days I lead Data Analytics at Snappr, a global photography marketplace. Like in any startup you end up doing a bit of everything: I've built data pipelines and custom connectors, designed our dbt architecture, set up dashboards, managed Snowflake permissions and roles, built tools to give non-technical teammates direct access to data, and worked closely with ops, finance, and engineering to turn messy business processes into something measurable.

I'm a Data & ML Engineer with a background in Biomedical Engineering. I work in tech consulting, where I design and build data workflows and experiment with applying machine learning and GenAI in practical ways. I’m especially interested in LLMs, knowledge graphs, and making complex ideas easier to understand, sometimes with the help of pop culture. Outside of work, I love dancing, reading fiction, watching movies, and obsessing over Formula 1. I like finding creative ways to learn and teach, and I bring that spirit into every project or talk I’m part of.

I am Maris Botero, Data Science Engineer at Mercado Libre working at the intersection of data, intelligent systems, and creativity. My work focuses on building machine learning solutions and designing intelligent agents that transform data into useful decisions. I am especially interested in making AI more understandable, practical, and accessible through applied learning experiences. In addition to my technical work, I explore generative art as a way to unite code and creativity, creating visual experiences that connect technology with narrative. I also actively participate in technology communities, sharing knowledge through talks, workshops, and educational content. I believe technology should not only be powerful, but also transparent, creative, and people-centered. My goal is to help others not only use AI, but understand how to design and build it.

Mathematical Engineer with an MSc in Applied Mathematics (Universidad EAFIT) and 7+ years of experience as a Data Scientist and Machine Learning Engineer. Currently at Provectus, building LLM evaluation and optimization pipelines for document processing automation. Also 3+ years lecturing Advanced Analytics and foundational Mathematics at Universidad EAFIT. Specialized in designing and deploying AI solutions including LLM evaluation systems, computer vision models, recommendation systems, and end-to-end ML pipelines. AWS Certified Generative AI Developer and AWS Certified Machine Learning Specialty. Proficient in Python, AWS, and GCP, with experience in diverse domains including finance, agriculture, healthcare, and entertainment. Previous speaker at Tech Caribe Fest, Python Medellín, and Medellín AI. Passionate about continuous learning, knowledge sharing, arts and Kung Fu.

I'm a System Engineer from Universidad ORT Uruguay with a Master's degree in BigData. In addition I've two post-degrees, one in BigData Analytics and another in Artificial Intelligence. I am currently working as a Machine Learning Engineer at Nortal (prev. UruIT and Nearsure) and I am a professor at Universidad ORT Uruguay. I have an extensive experience in the development of Business Intelligence solutions for various clients in South America and the United States and since 2018 I have worked in several projects based on Artificial Intelligence in areas such as Computer Vision (CV), Natural Language Processing (NLP) and Audio Processing (AP), among others.

I'm a software engineer and builder with more than 11 years of experience creating products for startups across healthcare, fintech, real estate, and AI. I specialize in Python, TypeScript, backend architecture, and modern AI-driven development workflows. I enjoy turning complex ideas into real products that people can actually use. Beyond coding, I care deeply about engineering quality, developer experience, clean systems, and continuous learning. I'm also passionate about community and education. I've spoken at conferences like PyTexas 2026 and organize developer events and workshops as a Cursor Ambassador in Ecuador.

Hello! I am Natalia, a final-year Physics student at Universidad de Antioquia (Colombia), and I am currently taking an AI bootcamp. I am passionate about applying machine learning and data science to real-world problems, from physical systems to behavioral data. I believe physics teaches you to see the world through patterns and equations, and AI gives you the tools to act on them.

I'm Data Science Manager at Visa, where I lead artificial intelligence projects for the Andean region focused on turning machine learning and GenAI models into real products with business impact. My work centers on closing the gap between research and production: from designing models to deploying them as scalable systems used by banks and companies across multiple countries. My career has been a fast track through the tech ecosystem in Latin America, passing through companies like Mercado Libre and Rappi, where I worked on high-impact problems like fraud, real-time pricing, and large-scale distributed systems. In these roles I've designed high-performance APIs, production models, and platforms that operate on hundreds of millions of transactions. In parallel, I'm co-founder and COO of an AI startup focused on commercial training through speech-to-speech systems, where I'm building modern architectures integrating voice models, LLMs, and real-time systems. Beyond the professional side, I've always been motivated to build community and accelerate technological development in Colombia. I've been an assistant professor at Universidad de los Andes, taught hundreds of people about machine learning and Python systems, and participated in creating a new Data Science program in the country. My interest in speaking at PyCon Colombia comes from that same motivation: sharing real learnings on how to build AI systems in production, and contributing so more developers in the region can build world-class technology from Latin America.

I’m a ML Engineer with a background in Biomedical Engineering. Back in my later years of college, I started focusing on Biomedical Signal and Image Processing and its different applications. This, in turn, led me to develop a strong interest in machine learning, whose roots have been entangled with my dear Signal Processing from the beginning. Nowadays I spend my days shipping (or at least trying) ML models to production for diverse use cases, going from Computer Vision applications in traffic analysis, Drug Discovery using Deep learning based protein embeddings, and automating medical scribe applications using agentic AI

Chemical engineer from Universidad Nacional de Colombia and currently pursuing a master's in chemical engineering with a research focus. I mainly work with Python for mathematical modeling, simulations, data analysis, and developing useful tools in industrial or academic contexts. I'm currently focused on research into hydrogen production in syngas, combining multiscale modeling, molecular simulation, and machine learning. I also work at Exergia Code, where I develop software and technical content bridging chemical engineering and programming.

Backend Developer with 6+ years of experience designing and building systems. Proven ability to lead and manage teams, streamline development workflows, and solve technical challenges.

Pablo Restrepo is a Colombian software and ML engineer with over 11 years of experience building AI and software systems across Colombia, Germany, the UK, and the US. He is currently Machine Learning Lead at Loka, where he designs and deploys end-to-end GenAI solutions for global clients. Before Loka, he spent nearly four years at Netlight in Munich, leading GenAI initiatives in insurance, financial media, and semiconductor manufacturing, and almost six years at Sura in Medellín, ending as a Technical Lead. He holds a Master's in Informatics, specialized in Machine Learning, from the Technical University of Munich, consistently ranked among the top 15 worldwide in Computer Science, and a BSc in Computer Science from Universidad EAFIT. He is also a published researcher in NLP and has spoken at conferences and meetups across Germany, Sweden, Norway, and the US. His current obsession: how developers can stay excellent engineers and multiply their impact in an industry being reshaped by LLMs.

I am Raul Rodriguez Lopez and I have spent more than 12 years getting my hands dirty with data. I did not arrive at Artificial Intelligence because it was trendy — I arrived because after a decade moving millions of records by hand, designing ETLs, migrating banking cores, and building highly complex pipelines, I understood there was a radically better way to do things. My path started from the deepest level of data: I migrated the entire core of major products with DataStage, built data warehouses and dimensional models for the financial sector at companies like Banco Popular, Banco de Bogota, and Corredor Empresarial, automated ETL processes with Spark on AWS, and designed data architectures at Colfondos. Then I spent 3 and a half years at Banco de Bogotá, where I scaled from Data Engineer Lead to DataOps and MLOps Manager — leading teams, managing cloud budgets, implementing CI/CD, and taking data culture to another level. Today I am Technical Lead at Mercado Libre, one of the largest tech companies in Latin America. I design multi-cloud architectures, build multi-agent systems with Generative AI using LLMs, ADK, LiteLLM, and Model Context Protocols (MCPs), and lead research into new technological capabilities for the business. But what truly transformed me was not a promotion — it was a mindset shift. I adopted an AI-First philosophy: if a task can be enhanced, delegated, or automated with AI, there is no reason to do it the traditional way. That mindset led me to create NORTH, a methodology I have been iterating in real production, where Claude is not a chatbot I ask questions to — it is a copilot that maintains the context of my projects, proposes architectural decisions, manages backlog, and synchronizes the state of everything I build. I develop custom skills, automate flows with agents, and every day I find a new way to amplify what I can do as an engineer. This is my first time as a speaker and I am not afraid to say it. I come with something no veteran speaker has: a real transformation story, from moving data with shell scripts in 2011 to orchestrating intelligent agents in 2026. I am not here to talk theory — I am here to show how a Colombian engineer, trained at SENA and Universidad Panamericana, came to lead AI at Mercado Libre by adopting a mindset anyone in this room can replicate. If you think AI is only for Silicon Valley, I am proof that you are wrong.

Ricardo Taborda is Dean of the School of Applied Sciences and Engineering at Universidad EAFIT, leading a school of 130 full-time faculty. His background combines academic administration with research in engineering seismology and earthquake engineering, including leadership roles in research organizations and international collaborations. He holds a Ph.D. in Civil Engineering from Carnegie Mellon University, a master's in Structural Mechanics from the University of Southern California, a master's in Structural Engineering from UNAM, and a bachelor's in Civil Engineering from Universidad EAFIT. He is skilled in scientific computing with a focus on computational seismology.

PyCon Colombia has been part of my professional growth in a concrete way: I presented workshops at the 2024 and 2025 editions, and each time I confirmed that this community has a real appetite for learning things they can apply the very next day at work. My path in technology did not start in AI or LLMs. It started providing technical support in the Colombian Air Force, teaching in classrooms, writing software tests, automating processes with RPA. That journey gave me something I value more than any framework: the ability to translate real problems into solutions that people understand and can operate. Today, as an Automation Engineer at Nowbit, that same principle guides the work we do building RAG systems, AI pipelines, and Python automations on AWS, Azure, and Elastic. This year I want to present without the backing of a sponsor — on my own conviction and on behalf of Nowbit. The topic I propose comes directly from what we experience in production: teams that manage to get an LLM working but do not know how much it costs them, why it fails, or how to improve it. LLM system observability with Python, OpenTelemetry, and Elasticsearch is not an academic topic for me — it is something we have had to build and learn along the way. I believe PyCon Colombia deserves more voices speaking from real practice, from Colombian projects, from error and adjustment. That is what I want to contribute.

I'm a Software Engineer focused on developer tooling, maintainability, and high-performance systems, with a strong interest in the Python and Rust ecosystems. I'm the creator of complexipy, an open source cognitive complexity analyzer for Python written in Rust, designed to provide fast local feedback for developers and CI pipelines. I've also contributed to open source projects including Rust and other developer tooling initiatives. My work focuses on building tools that help engineers write more maintainable and reliable software.

Sankalp Gilda, PhD (Astrophysics, University of Florida, 2021). Staff Machine Learning Engineer at DeepThought Solutions, where he leads work on production AI evaluation tooling, host-side instrumentation for agentic execution sandboxes, and LLM-based knowledge-graph extraction. Author of tsbootstrap, an open-source Python library for time-series bootstrapping. Previously built ML systems at Marathon Petroleum, Fermata Energy, and the Canada-France-Hawaii Telescope. Recent academic work: ICML 2026 position paper on epistemic accountability for AI-assisted engineering (under review), ICLR 2026 Advances in Financial AI, and LLM Logical Reasoning workshops (accepted).

Santos is a software and application security engineer from Ecuador, currently working at Read the Docs. Passionate about web development, Python, cybersecurity, and open source. Santos has reported vulnerabilities in several projects including Neovim, GitPython, django-allauth, Sentry, and more. When he's not in front of a screen, you can find him reading, painting, enjoying metal concerts, or rock climbing.

Biomedical engineer from Universidad de los Andes, with a minor in neuroscience and an MSc in biomedical engineering focused on machine learning. Currently working as a machine learning engineer building production AI systems, extraction pipelines, and conversational agents. Python was my first programming language and the one where I learned how to think in code, not just write it. For the past two and a half years I was a teaching assistant for ML fundamentals at Los Andes, a role that reinforced a conviction I'll happily defend on stage: complexity is rarely the answer and almost always the excuse. When I'm not at a keyboard, I'm on a football field.