Miguel Barros

Miguel Ángel Barros Núñez · Colombia / UTC−5

Complex data.
Reliable systems.

Systems engineer with 8+ years of experience in software development. My profile brings together backend, data, full-stack development, machine learning and agentic AI.

Miguel Ángel Barros Núñez
Miguel BarrosSOFTWARE ENGINEERING & AI
TECH STACKExplore all ↗
  • Python
  • Java
  • .NET
  • Go
  • TypeScript
  • Docker

01 / Selected work

Engineering in practice.

Enterprise software, digital products and research. A selection of the problems I work on.

01 / ENTERPRISE SOFTWAREWEB + API
Conceptual view of system modules

Operations / Traceability

Asset management across locations

An inventory platform that brings together assignments, geographic catalogs and reporting, with electronic waste traceability.

APIRelational DBAccess controlWeb
Explore technical approach
  • Vertical-slice architecture, organized by functionality.
  • Four-level RBAC, scoped by location in backend and frontend.
  • Barcode scanning, Excel import, PDF/Excel reports and QR labels.
02 / DIGITAL COMMERCEWEB + API
FashionHouseCATALOG · ORDERS · CUSTOMERS
Web→API→DB + Storage

Product / Full stack

A connected boutique operation

Catalog, purchases, made-to-measure orders and customer relationships, connected through a backend API.

BackendWebDatabaseContainers
Explore architecture
  • Web storefront connected to a backend API.
  • Relational database and object storage.
  • Container-based delivery.
View repository ↗

03 / Reference architecture

Multi-source ETL pipeline

A reference design to consolidate databases, APIs and files into a validated central data model.

Read design details
  • Batch processing with restart and skip policies.
  • Staging tables and idempotent upserts for safe re-runs.
  • Rejected records with reason codes and per-run auditing.

04 / MSc research · In progress

AI for industrial processes

Research on deep learning and flow analysis for detecting bottlenecks in industrial processes, as part of my MSc in AI at UNIR.

Read research focus

The thesis focuses on the design and implementation of deep learning and flow analysis techniques. Research is ongoing; results are not yet presented here.

Open source / Exploration

Exploring AI integrations

Forks of third-party projects with proposed use cases. Personal implementations are not yet complete.

Fork / Proposed use case

Spring AI

Explore how to turn support requests into structured tickets through a backend API, with field validation and human review.

JavaIA / AIAPI
Fork / Proposed use case

Docling

Explore the conversion of synthetic delivery documents into structured inventory data, checking fields, table rows and traceability.

PythonDocumentsData
Also built: FichaMedida — digital measurement sheets for tailors.Code ↗

02 / Experience

From data
to delivery.

Currently a Senior AI Engineer at Canadian Tech Forge, while continuing my independent software consulting practice.

Canadian Tech Forge

Senior AI Engineer

AI-assisted software development with coding agents: architecture, workflow design and validation of generated code, from implementation to deployment.

Independent Consulting

Software Engineer / Consultant

Ongoing independent consulting alongside my role at Canadian Tech Forge: software architecture, APIs, integrations and end-to-end delivery for clients.

Thomas Greg & Sons

Backend Software Engineer

ETL pipelines, backend modules for electoral applications and cloud microservices.

Transportes Sánchez Polo

Backend Developer

Backend development and enterprise integrations in collaboration with distributed teams.

ISES S.A.S.

Analyst Developer / Cartographic Manager

Relational data analysis with PL/SQL and business intelligence with Tableau.

03 / Capabilities & background

PROFILE.

Software engineering and artificial intelligence. I combine experience in backend, data and full-stack development with knowledge of machine learning and agentic AI.

Education / 2014

Systems Engineering

Universidad Simón Bolívar

In progress / Expected 2027

Master’s in Artificial Intelligence

UNIR · Spain

01

Machine Learning

Knowledge of machine learning and deep learning, connected with data analysis and my research on industrial processes.

02

Agentic AI

Knowledge of agentic AI: agents, tool use and workflows for addressing multi-step tasks.

03

Full-Stack Craft

Web product development connecting interfaces, backend services and databases, from architecture to deployment.

04

Backend & APIs

Services, business logic and integrations connecting applications with business operations.

05

Data & Integration

Database modeling, ETL processing and data flows with validation and traceability.

Spanish / Native · English / B2

Tech Stack

Tools I use

Languages

(06)
  • Python
  • Java
  • C#
  • Go
  • TypeScript
  • SQL

Frameworks & libraries

(10)
  • FastAPI
  • Django
  • pandas
  • Spring Boot
  • Hibernate
  • ASP.NET Core
  • EF Core
  • Gin
  • GORM
  • Next.js

Databases

(05)
  • PostgreSQL
  • Oracle
  • SQL Server
  • MySQL
  • MongoDB

Tools & cloud

(03)
  • Docker
  • GitHub Actions
  • Azure

04 / Let's connect

Your next challenge.
Let's build it together.