Principal Software Engineer · Platform Architect · AI Systems
I build platforms that turn fragmented data, integrations, and processes into operational intelligence — and lead the teams and architecture behind them.
Software engineer, platform architect, and technical leader with 15+ years designing, building, and operating the platforms that companies run on — multi-tenant SaaS, distributed systems, large-scale data acquisition, and AI-native products.
One thread connects the work across fintech, legaltech, retail & commerce intelligence, and data-intensive platforms: taking fragmented data, integrations, and processes and turning them into operational intelligence — systems a business operates on, not dashboards it looks at. I did it consolidating millions of pricing signals for global brands; I'm doing it now in DevShell Tech, where many products share one foundation.
I operate across the full arc — set the architecture and strategy, then write the code that de-risks the hardest parts — and I treat structural decisions as business decisions: every one tied to cost, reliability, or speed-to-market.
DevShell Tech — a platform where one shared foundation powers many products and verticals, instead of rebuilding infrastructure, data, and AI for each. It spans an infrastructure control plane, a multi-tenant runtime, universal connectors, data acquisition at scale, workflow automation, and a native AI layer. The point isn't the parts — it's that the cost of the next product, vertical, or tenant keeps falling.
↑ Mapped from the real system I architect and operate (vision → products → domains → capabilities → projects) — explore it live.
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Oracle — Hub — |
Datahouse — Ella — |
The kinds of systems I design and own end-to-end — each framed by the problem it solves, not the stack it runs on.
| Domain | What it does for the business |
|---|---|
| Multi-tenant SaaS | One platform serving many customers and verticals — new products ship as modules, not rewrites. |
| Data acquisition at scale | Reliable supply of external data when the web fights back — the raw material for any intelligence. |
| Integration ecosystems | Many systems made to behave as one, on a single canonical data model — no more silos that disagree. |
| AI & agentic systems | AI that understands the whole operation and can act on it — function by conversation, decisions with context. |
| Operational intelligence | Fragmented signals turned into what to do next — pricing, shelf, performance, growth. |
| Reliability & cost | Systems easier to operate than to explain — observable, resilient, and cheaper to run over time. |
- Designed and operate DevShell Tech end-to-end — control plane, data acquisition, integration framework, workflow automation, AI layer, and vertical apps — proving one foundation can power many products at a falling marginal cost.
- Built retail & commerce-intelligence platforms processing millions of pricing, inventory, and merchandising signals across global marketplaces, used by global consumer brands to steer pricing, availability, and digital-shelf strategy.
- Architected large-scale, cost-efficient web-access and data-acquisition infrastructure with reliability and observability as first-class concerns — cutting operational spend without sacrificing quality.
- Delivered high-volume payments and financial systems under strict reliability and compliance constraints, at one of Latin America's largest acquirers.
- The consistent thread across fintech, legaltech, retail intelligence, and data platforms: turning fragmented data, integrations, and processes into operational intelligence.
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timeline
title Professional Journey
2011 : CS-Consoft — Software Developer
2012 : BLM — Ecommerce Manager : RS Websites — PHP Developer
2014 : Orgamec — PHP Developer : Contalex — Java Fullstack
2018 : Zoroastro — Fullstack Developer
2019 : Intellibrand — Fullstack Developer
2021 : Intellibrand — Technical Lead
2023 : Ascential — Technology Manager : Stone — Senior SWE
2024 : Jusbrasil — Senior SWE
2025 : Visualitics — Senior SWE
Now : Founder — Platform Architect
Different industries, one trajectory: from building data and commerce-intelligence platforms for global brands, to owning the architecture of DevShell Tech. The constant is platforms, data, integrations, and operational intelligence — each role a deeper cut at the same problem.
Founder & Platform Architect — DevShell Tech · 2023–Present
Built: DevShell Tech — a single platform where one shared foundation powers many products: control plane, data acquisition, integration framework, workflow automation, native AI layer, and vertical apps. Problem: every new product or vertical normally means rebuilding infrastructure, data, and AI from scratch. Impact: verticals now ship as modules on a shared base, so the marginal cost of the next product, tenant, or market keeps falling — and the AI understands the whole operation because everything lives on one data model.
Ownership across architecture, product strategy, infrastructure, AI systems, data platforms, and engineering standards.
TypeScript · Node.js · Next.js · PostgreSQL · Redis · Kubernetes · local LLMs · event-driven architecture
Senior Software Engineer — Visualitics · 2025–Present
Built: the integration and processing core of a commerce-intelligence platform that consolidates marketplace, advertising, and analytics data into a single decision layer — surfaced in-workflow through web apps and a browser extension. Problem: sellers' performance data is scattered across a dozen marketplaces and ad networks that never agree. Impact: one place to see and act on the whole operation, with insight delivered where the work already happens.
Owned multi-source ingestion, distributed processing, ETL, and KPI computation across Mercado Livre, Shopee, Amazon, VTEX, NuvemShop, GA4, Meta and Google Ads.
Node.js · TypeScript · FastAPI · BigQuery · Redis · GCP · browser-extension architecture
Senior Software Engineer — Jusbrasil · 2024–2025
Built: the large-scale web-access and data-acquisition infrastructure behind the company's intelligence operations — proxy and routing architecture for fast, dependable retrieval at scale. Problem: reliable data acquisition gets expensive and brittle as volume and anti-bot pressure grow. Impact: materially lower operational spend with stronger reliability — and internal tooling that lifted the whole team's throughput.
Reliability, resiliency, observability, and developer-experience work as first-class concerns.
Node.js · TypeScript · Kubernetes · Redis · PostgreSQL · observability platforms
Senior Software Engineer — Stone · 2023–2024
Built: backend services and integrations for high-volume payment processing and merchant acquiring at one of Latin America's largest acquirers. Problem: money movement tolerates no downtime, no data loss, and no compliance gaps — at scale. Impact: dependable, low-latency financial flows that hold under strict reliability and regulatory constraints.
Distributed systems, payment and banking integrations, and performance optimization under fintech-grade requirements.
Node.js · TypeScript · distributed systems · cloud infrastructure
Technology Manager — Ascential · 2023
Led: engineering for the digital commerce-intelligence platforms used by global consumer brands — architecture, data pipelines, analytics, and cloud infrastructure for large-scale retail data. Problem: global brands can't see how they're really performing across thousands of digital shelves. Impact: enabled those brands to optimize pricing, availability, search visibility, and digital-shelf performance — set the roadmap and the quality and operational standards behind it.
Engineering leadership across retail analytics, content & compliance, and store-locator tooling.
Distributed data platforms · analytics pipelines · cloud infrastructure
Technical Lead → Fullstack Developer — Intellibrand · 2019–2023
Built & led: large-scale retail-intelligence platforms processing millions of pricing, inventory, and merchandising signals across global retailers and marketplaces — as Tech Lead, owned scalability, data ingestion, pricing intelligence, and digital-shelf analytics. Problem: pricing and shelf decisions were made blind, across too many channels to track by hand. Impact: turned a flood of fragmented signals into real-time intelligence brands could act on — and grew the engineering team and standards that sustained it.
Where the through-line started: fragmented data → operational intelligence, at scale.
Node.js · TypeScript · data pipelines · cloud · AI/ML
Earlier career — 2011–2019
| Company | Role | Focus |
|---|---|---|
| Zoroastro Advogados | Fullstack Developer | Legal ops, workflow automation, financial systems (Node, Angular, Mongo) |
| Contalex | Java Web Fullstack | ERP SaaS for accounting firms (Java, Spring, Hibernate) |
| Orgamec | PHP Developer | Internal business-process automation |
| RS Websites | PHP Developer | Web apps, systems, and ERP (PHP, Laravel, MySQL) |
| BLM | Ecommerce Manager | Digital commerce + a geolocation/Bluetooth Android app |
| CS-Consoft | Developer | Desktop / RIA software |
- Full-arc ownership — set architecture and technical strategy, then write the code that de-risks the hardest parts. I don't hand off the unknown.
- Force-multiplier engineering — establish the standards, review culture, and platform conventions that let a small team ship like a much larger one.
- Grew people and direction — mentored engineers and owned roadmaps and technical decisions as Tech Lead and Technology Manager.
- Architecture as a business lever — every structural decision tied to a concrete outcome: lower cost, higher reliability, or faster time-to-market.
| Platforms | Multi-tenant SaaS · distributed & event-driven systems · domain-driven design · system design |
| Data & integration | Connector frameworks · canonical data modeling · ETL & analytical pipelines · large-scale acquisition |
| AI-native | Agentic systems · retrieval-augmented generation · knowledge systems · vector search · local-first inference |
| Operations | Reliability & observability · cost engineering · infrastructure as a shared control plane |
Languages
Frontend
Backend
Data
Infrastructure
AI & Automation
Simple scales.
Architecture is a business decision.
Operational excellence beats cleverness.
Data is a platform, not a byproduct.
AI should amplify humans.
Build systems that are easier to operate than to explain.
Designing systems that outlive the applications built on top of them.
Open to conversations with recruiters, partners, and prospective co-founders.
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