“Engineering is the art of understanding complex systems.”
I'm Sebastián López Osorno, a developer from Medellín, Colombia, in my final semester of Computer Engineering. For more than 4 years I've been getting systems that don't talk to each other to share data people can trust.
I started in data as an intern at Quipux, with ETL routines, automated reports and KPI dashboards for revenue collection, plus Python scripts to track campaigns and clean up databases. At MUV-U I built the Power BI reports for finance, sales and marketing, and later designed how data enters the CRM.
Before I build a dashboard I want to know which decision it supports and where each figure comes from. At TIVENOS I write Zoho Analytics dashboards in SQL and run bulk extracts of the CRM into PostgreSQL to analyze it outside of it. The next step is to formalize it with a specialization in data science.
Along that path I've worked on almost every side of a tech team, from data, CRM and backend to frontend, servers and, at TIVENOS, technical coordination. It lets me understand what marketing, finance or IT ask for without anyone translating it for me, and turn it into concrete tasks.
With artificial intelligence I took the same path, from building it to directing it. At university I built, with a classmate, an expert system in CLIPS, fuzzy logic with scikit-fuzzy and genetic algorithms, and on my own a reactive agent that decides which actuators to switch on; at SmartPot, an assistant with expert rules, fuzzy logic and scikit-learn models that forecasts when a crop will leave its range and proposes actions applied in bulk; and at ADCOM, lead contact with AI agents in Dapta.
I work with language models at both scales. On the small side, I fine-tuned Qwen2.5-1.5B with LoRA and built a RAG pipeline with a quantized Qwen2-0.5B and a FAISS index, meant to run on modest hardware. On the large side, I built an n8n agent that answers with Claude and queries three MCP servers I wrote in Python, and I've worked with GPT, with Gemini and with open models running locally through Ollama.
In daily development I direct coding agents, Claude Code among them, with engineering judgment. Before delegating I write down each project's rules, from commit authorship to what is never touched in production; then I review every proposal and run it through the same tests and the same CI as any other change. Having built these systems from the inside is what lets me decide what to delegate, spot when an answer doesn't hold up and use AI to save work without giving up the design.
Next is bringing those language models to the data I integrate today, with assistants that answer from each organization's own information. On the academic side, I finish the cybersecurity diploma in December 2026, graduate in March 2027, and then come a specialization in data science and a master's in cybersecurity.
What I care about most is finance, sales and marketing deciding with the same figure. I'm looking for a data or BI role where analysis ends in a decision, remote or hybrid.
