01
Software Architecture
System design grounded in business constraints, operational reality and explicit trade-offs.
- Distributed systems
- Event-driven architecture
- Hexagonal architecture
- ADRs & system design
Tech Lead · Senior Java Engineer
I design systems that stay fast, resilient and understandable at scale.
I connect architecture, hands-on engineering and technical leadership to turn complex business problems into reliable production systems.
profile.overview
open to global teams
ENGINEERING PATH
- 01ArchitectureContext · Constraints · Trade-offs
- 02EngineeringJava · Cloud · Distributed Systems
- 03ProductionReliability · Observability · Scale
01 / EXPERTISE
Engineering depth.
Leadership perspective.
My role is not only to choose technologies. It is to create clarity, reduce risk and help teams deliver systems that behave well in production.
02
Java Engineering
Modern backend platforms with performance, maintainability and pragmatic evolution in mind.
03
Production Reliability
Resilience and observability designed as architecture capabilities, not production afterthoughts.
04
Technical Leadership
Connecting engineers, product and platform teams around decisions, quality and sustainable delivery.
02 / SELECTED WORK
Problems worth solving.
Labs and products built to make architecture choices visible: context, constraints, implementation, failure modes and results.
In development
AI ENGINEERING
FEATURED PROJECT
ATLAS
AI Tech Lead Assistant
An engineering copilot for architecture analysis, troubleshooting, documentation and code intelligence—kept outside the transactional core.
JavaLLMRAGMCPVector DB
Planned
PERFORMANCE
High-Throughput
Java Lab
Benchmarking concurrency, caching and messaging decisions under realistic load and failure scenarios.
FocusLatency
RuntimeJava 21
MethodLoad tests
Planned
RELIABILITY
Production
Resilience Lab
Timeout, retry, circuit breaker, bulkhead, idempotency and DLQ tested through controlled failure injection.
Product discovery
SAAS
MatilhaOS
Cloud-native daycare operations platform connecting product discovery, scalable architecture and delivery.
MVP→Architecture→Cloud→Scale
03 / EXPERIENCE
Leading from design
to production.
CURRENT
Tech Lead · Equifax
Technical leadership for credit platform services, driving Java modernization, reliability, observability and architectural evolution across teams.
PREVIOUS
Systems Specialist · Getnet / Santander
Hands-on engineering and technical leadership in financial technology, connecting product goals to secure and maintainable backend platforms.
FOUNDATION
15+ years building technology
From software development to architecture and leadership, with a consistent focus on backend engineering and business-critical systems.
04 / ENGINEERING DECISIONS
Technology choices need context.
I evaluate options by workload, team maturity, failure modes, operational cost and the ability to evolve—not by trend.
01Modular Monolith vs Microservices+
Start with boundaries, not deployment units. Microservices earn their place when independent scaling, ownership or release cadence creates measurable value.
BOUNDARIES · OWNERSHIP · OPERATIONAL COST02Virtual Threads vs Reactive+
Virtual threads simplify high-concurrency blocking workloads. Reactive remains valuable where end-to-end streaming and backpressure are core requirements.
CONCURRENCY · COMPLEXITY · BACKPRESSURE03Kafka vs Traditional Queues+
Kafka fits replay, high event volume and ordered processing by key. Traditional brokers often reduce complexity for command-style queues and routing-heavy flows.
REPLAY · ORDERING · DELIVERY SEMANTICS04SQL vs NoSQL+
Choose from access patterns and consistency needs. Relational databases remain a strong default; specialized NoSQL models solve specific scale and shape constraints.
CONSISTENCY · ACCESS PATTERNS · DATA SHAPE05 / LET’S CONNECT
Complex systems.
Clear decisions.
I’m open to conversations about technical leadership, Java platforms, distributed systems and international engineering opportunities.
Based in São Paulo, Brazil