End-to-End Ownership: Leading the full lifecycle of mission-critical security and identity flows, from initial requirement gathering with global stakeholders to final release and post-launch monitoring.

AI-Driven Development: Optimizing software delivery lifecycles by integrating Claude Code and autonomous AI agents to automate boilerplate generation, unit testing, and complex refactoring, significantly increasing development velocity.

LLM Integration: Leveraging Large Language Models to build data-driven features, delivering rapid user-centric value and sophisticated processing in high-density data environments.

Microservices Migration: Leading the architectural transition of mission-critical identity verification and security flows from a Ruby on Rails monolith to a high-performance Golang ecosystem.

System Design: Implementing robust APIs using gRPC and GraphQL, ensuring low-latency communication for millions of global users.

Mercado Livre is the leading provider of technology for e-commerce in Latin America, with a pretty high volume of transactions and packages delivered by day in many countries.

Some meaningful achievements:

• Successfully migrated an application to a new microservice architecture utilizing Golang, MySQL, KVS, Redis, pub/sub queues, and implementing comprehensive testing strategies including unit and integration tests, achieving over 95% test coverage. This high-quality microservice is dedicated to aggregating logistics travel data from diverse sources such as package arrivals and vehicle GPS locations, accessible via a REST API. Handling a substantial volume, the microservice manages 11M messages and 500k HTTP requests daily, enhancing data accessibility and system reliability. Monitoring of the system is ensured through New Relic, Datadog, and Grafana to track performance and troubleshoot issues.

• Implemented goroutines in Golang to significantly boost the performance of a large-scale report generation task. By leveraging goroutines for concurrent data fetching and object construction, the processing time was dramatically reduced by approximately 90%, from an average of 10 seconds to just 1 second.

• Successfully redesigned date filters for the travel search API, encompassing multiple date types within a single request. This multifaceted project engaged cross-functional collaboration with teams including UX, product, end-users, and technical experts. The outcome introduced a new standard of filters, empowering users with increased autonomy while streamlining backend processes for improved maintenance and performance.

ContaAzul is one of "LinkedIn Top Startups 2018" in Brazil.

Working on the accountant dashboard team, i was responsible for building the application that connected an accountant with its Conta Azul customers, allowing the accountant to take actions such as exporting customers financial data, activate/deactivate features and plans of its customers, monitor the use of the platform by customers, etc.

Working at this team i had a lot of integrations with product, data and customer success teams to maintain old features and build the new ones.

I was responsible of implementations on a Java monolith application and several Java microservices around it, all of them with a high test coverage, with unit and integrations tests.

Some meaningful achievements:

• Led the maintenance and implementation of new features on a Golang microservice responsible for seamless integration between an accountant platform and a third-party educational tool. Utilized technologies including PostgreSQL, Amazon SQS, Amazon SNS, Kubernetes, and Lambda functions to efficiently manage and process data, including handling webhooks from the third-party application. This integration significantly contributed to educating over 10,000 accountants.

• Developed a comprehensive platform tasked with identifying payments made by ContaAzul customers referred by accountants, aggregating commissions based on the accountant's partner level, and managing the tracking, payment, and expiration of these commissions. This microservice was implemented using Java, Spring, PostgreSQL, Amazon SQS, and Amazon SNS.