Azar'Tharion-Nox Let’s talk ↗

✳ AI AUTOMATION & BACKEND ENGINEERING

Built for complexity.
Designed to last.

I turn complex operations into reliable AI systems,
connected workflows and dependable infrastructure.

Discuss a project ↗Explore my work ↓
Senior Automation Engineer at EngineCampinas, Brazil · Working globallySCROLL TO EXPLORE ↓
01 / SELECTED WORKFROM COMPLEXITY TO CLARITY

The systems behind
the outcomes.

A selection of the AI, automation and data work
I’ve delivered across client and engineering roles.

AI SYSTEMS / LEARNPEST01 ↗

Answers, with a process behind them.

A multi-agent workflow for routing internal questions through retrieval, specialist reasoning and evaluation.

Conceptual AI workflow: internal query; 01 Classifier — understand intent; 02 Retrieval — find context; 03 Specialist — develop an answer; 04 Evaluator — check the output; reviewed answer.
Python · n8n · LLM orchestration2025—2026
Explore the approach +
01 / THE PROBLEM

Make internal knowledge usable.

Support internal questions with a workflow that brings together intent routing, retrieval, specialist reasoning and evaluation.

02 / MY CONTRIBUTION

One workflow. Four focused agents.

  • Designed the classifier, retrieval, specialist and evaluator workflow.
  • Built LLM integrations and external-data processing with n8n and custom Python scripts.
03 / REPORTED RESULTS
90%Internal-query resolution
75%Faster delivery
40%Lower processing latency

Self-reported results from my LearnPest role.

DATA ENGINEERING / GALAPAGOS CAPITAL02 ↗

Operational data. Put to work.

Backend tools and ingestion pipelines shaped around financial, compliance and operational requirements.

Conceptual data flow: applications and external data; 01 Ingest — collect the data; 02 Process — structure and transform; 03 Deliver — support operations through internal tools and analytics.
ETL · Backend tools · Integration2024—2025
Explore the approach +
01 / THE PROBLEM

Connect data to daily operations.

Bring complex programmatic data into the tools teams use for financial, compliance and operational work.

02 / MY CONTRIBUTION

From ingestion to internal tools.

  • Developed backend tools and automated web applications.
  • Engineered data-ingestion pipelines to support real-time analytics.
03 / DELIVERY FOCUS
Data ingestionBackend toolingOperational applications

Connected data infrastructure with the financial and operational requirements it needed to serve.

ALSO IN MY PRACTICE

Relational data architecture and integrations at Eluvi. Custom B2B applications and automation through Azar'Tharion Nox.

02 / HOW I CAN HELPTHE RIGHT SYSTEM FOR THE REAL PROBLEM

Less friction.
More capability.

For teams connecting fragmented tools,
scaling a workflow or bringing AI into production.

Three engineering services illustrated in glass and violet light: AI systems for reasoning, retrieval and evaluation; backend integrations using APIs, data models and connections; data automation for ingestion, processing and workflows.
01 /

AI systems &
agentic workflows

Give your team a useful way to work with its information. I design retrieval, routing and evaluation workflows around your data, constraints and intended outcomes.

  • Retrieval-augmented generation
  • Multi-agent orchestration
  • LLM integrations & evaluation
02 /

Backend &
integrations

Connect the tools your operation depends on. I build APIs, data models and integrations that turn disconnected applications into a coherent workflow.

  • APIs & custom webhooks
  • Relational data architecture
  • Operational applications
03 /

Data pipelines &
automation

Move information where it needs to go and reduce repetitive work. I build ingestion and processing pipelines shaped around the people and systems using them.

  • ETL & data ingestion
  • Workflow orchestration
  • Existing-system optimization
03 / THE APPROACHINTENT → ARCHITECTURE → DELIVERY

Understand deeply.
Build deliberately.

The implementation starts with the operation:
what needs to happen, what can fail and what success means.

Four engineering stages: 01 Define — understand the problem; 02 Design — shape the architecture; 03 Build — implement and evaluate; 04 Evolve — prepare for day two.
  1. 01

    Define the problem

    Map the workflow, constraints and desired outcome. Make the important assumptions explicit.

  2. 02

    Design the system

    Choose clear boundaries, data flows and integrations. Make the architecture fit the problem.

  3. 03

    Build & evaluate

    Implement in focused stages. Check behavior against realistic inputs and expected failure cases.

  4. 04

    Prepare for day two

    Make the system understandable and maintainable, with a clear handoff and room to evolve.

04 / THE PERSON BEHIND THE SYSTEMSBRAZIL / GLOBAL
Aldric Azar'Tharion-Nox. Thoughtful systems. Lasting intent. A signature sculpture combining black basalt, architectural glass and violet light.

ALDRIC

Azar'Tharion-Nox.

An engineering practice built on curiosity,
ownership and thoughtful execution.

I’m an automation and AI engineer based in Campinas, Brazil. My work has grown from building web applications and low-code products to designing integrations, data infrastructure and agentic workflows.

I work across the gap between what a business needs and what its systems can actually do—combining practical delivery experience with a focus on clear architecture.

My professional experience is currently listed on LinkedIn as Silas Neto.

Connect on LinkedIn ↗

Experience, in perspective.

Building and delivering since 2020.

2026—PRESENT

Engine

Senior Automation Engineer

2021—PRESENT

Azar'Tharion Nox

Founder · Web applications, automation & AI

2025—2026

HireMango / LearnPest

AI solutions & automation engineering

2024—2025

Galapagos Capital

Automation & Data Engineer

2024

Eluvi

Software & Infrastructure Engineer

View earlier roles & complete dates +
  • Engine: Senior Automation Engineer, May 2026–Present.
  • Azar'Tharion Nox: Founder / AI Specialist, September 2024–Present; Founder / Automation Specialist, February 2023–September 2024; Founder / Low-Code Developer, August 2021–February 2023.
  • HireMango: Senior AI Solutions Developer, July 2025–February 2026.
  • LearnPest: Senior AI Automation Engineer, July 2025–February 2026.
  • Galapagos Capital: Automation & Data Engineer, September 2024–June 2025.
  • Eluvi: Software & Infrastructure Engineer, January–November 2024.
  • Web3Fast: Junior Web Developer, November 2021–December 2022.
  • OVG Consultoria: Trainee Web Developer – Bubble, March 2020–November 2021.

Some roles ran concurrently. The dates above follow my current LinkedIn profile.

05 / NOTES ON ENGINEERINGIDEAS BEHIND THE IMPLEMENTATION

Beyond the build.

Thoughts on the choices that make
systems useful, maintainable and resilient.

Three editorial themes: Architecture — design for day two; Local AI — fewer moving parts; Agentic systems — build for resilience. Illustrated as glass and stone architectural studies.
01 / ARCHITECTURE

The work begins after generation.

On portability, ownership and designing software for day two.

↗02 / LOCAL AI

A leaner path through RAG.

Local embeddings, in-memory retrieval and fewer moving parts.

↗03 / AGENTIC SYSTEMS

Design for the moment something fails.

Moving from linear scripts toward workflows that can recover.

↗

Editorial summaries · Original writing on LinkedIn ↗

06 / START A CONVERSATIONCLARITY STARTS WITH A GOOD QUESTION

What could work
better?

Tell me what your team is trying to build, connect or improve.
A short description of the problem is a good place to start.

Discuss your project ↗
Campinas, Brazil / UTC−3English · Português · EspañolLinkedIn ↗