Miguel Ribeiro / Automation · Software · Cloud
I build automation, data workflows and Python-backed applications around the way people actually work. My background in operations helps me understand the problem before choosing the technical solution.
The through line
Operational understanding.
Practical engineering.
Systems people can use.
01 / Selected work
Each case study explains the context, the engineering approach and what came out of the work.
An Excel/VBA ETL and reporting automation for Cisco Asset Management that evolved into Python-backed processing in an internal application.
Read case studyA Python document-processing and retrieval tool that made information from more than 700 DOCX files accessible through search and an AI-assisted interface.
Read case studyA personal place-to-live review platform for sharing experiences at specific locations, built with a Python backend, React frontend, and Azure deployment.
Read case studyA public AI courtroom app that turns everyday disagreements into humorous rulings, built with React, Python Azure Functions, Google GenAI, and PostgreSQL.
Read case studyA human-directed, repository-driven AI-assisted long-form fiction experiment. Manuscript, plans, continuity state, and agent instructions live together so a chapter can begin from a minimal task prompt.
Read case study02 / Portfolio engineering
A deployed Django application, not a static résumé page. I use it to put web development, delivery and AI integration into practice.
Django and PostgreSQL power responsive project case studies. Portfolio content is version controlled and synced through an idempotent Django management command.
Docker Compose runs the local app. Automated Django tests run in PostgreSQL-backed GitHub Actions CI; feature branches and pull requests lead to Railway deployment with environment-based production configuration.
The Google Gemini assistant answers from curated portfolio context and public project records. Its credentials stay server-side.
03 / Areas of work
My work connects operational needs with tools that make information easier to process, find and use.
Turning manual reporting and document workflows into repeatable Python-backed processes.
Building applications that validate inputs, process data and give people useful feedback.
I run this Django/PostgreSQL portfolio with Docker Compose locally and deploy it to Railway after GitHub Actions CI passes. Other public projects run on Azure Static Web Apps and Functions.
I build Google GenAI conversational interfaces, including this portfolio's grounded assistant and The Judge's structured rulings. Credentials stay server-side, and Python validates The Judge's verdict before the UI displays it.
04 / About
I started my career in professional kitchens, then moved into IT through networking and cybersecurity training. I now work in Cisco Asset Management, where I have built software and automation around operational problems.
That path shapes how I approach a project. I start by learning how the work happens and where people lose time or context. From there, I decide what should be automated, what needs a clearer interface, and where a reliable backend can help. My projects span reporting workflows, document processing, web applications and AI-assisted tools. I am continuing to deepen my software, cloud, automation and infrastructure engineering skills, with a focus on systems that hold up beyond a demo.
05 / Contact
I'd be glad to talk about automation, software, AI-assisted systems or practical engineering problems.