Software engineer focused on backend architecture, applied AI, and the design of reusable delivery systems.

I build software, but I am especially interested in building the systems that help software get built well.

My current work sits at the intersection of:

• backend architecture
• AI-assisted engineering workflows
• spec-driven delivery
• internal developer frameworks
• turning messy business rules into clear operational systems

• reducing ambiguity before implementation
• preserving context across sessions, collaborators, and tools
• creating engineering leverage through structure, not bureaucracy
• using AI as a real collaborator instead of a novelty layer
• shipping real products as validation, not just publishing ideas

Shipped psychology research application built with React, TypeScript, browser-side SQLite, and an embedded SDD workflow.

• Repository: meta-contingency-game
• Live app: codelib.com.br/app

This project is a public validation case for a private internal SDD blueprint that I am evolving as part of a broader platform vision.

Public-safe Python CLI case study for legacy user migration, focused on CSV analysis, sanitation rules, SQL generation, and controlled PostgreSQL loading.

• Repository: pytool_migra_users

This project highlights backend-oriented migration engineering: data quality analysis, operational safety, and sanitized publication of a real internal tool.

Sanitized Python ETL case study for payroll migration, covering Oracle extraction, normalized PostgreSQL loading, pre-load diagnostics, and controlled cache refresh workflows.

• Repository: payroll-migration-engine

This project highlights deeper data engineering concerns: multi-stage ETL orchestration, idempotent loading, validation-first execution, and public-safe packaging of a complex internal migration system.

Sanitized AI-assisted legacy analysis workbench for PHP and SQL Server systems, combining static scanning, dependency tracing, schema inspection, UI flow analysis, and domain mapping.

• Repository: legacy-analysis-workbench

This project highlights higher-level engineering leverage: building internal instruments that help teams understand, diagnose, and modernize large legacy systems with structured AI assistance.

• building stronger public case studies around architecture and delivery systems
• refining private internal tooling for reusable SDD generation
• exploring practical human + AI collaboration patterns in real software projects
• investing in high-leverage engineering systems with product potential

• Backend & Systems: PHP, Laravel, Python, REST APIs, system design
• Frontend: React, TypeScript, JavaScript
• Data: MySQL, SQL Server, Power BI
• AI: applied AI, machine learning workflows, AI-native product thinking
• Tooling: Git, Docker, structured delivery workflows

I have over 12 years of experience working with backend architecture, legacy modernization, and real-world software delivery.

I am also pursuing a Master's degree in Artificial Intelligence, with a strong interest in intelligent systems that are useful outside the lab and durable inside production.

• LinkedIn: linkedin.com/in/pauloeremita
• Website: pauloeremita.com.br