I am a backend engineer with over 16 years of experience building high-throughput distributed systems. My expertise lies in event-driven architecture, CQRS, and Domain-Driven Design. Throughout my career, I have delivered data pipelines that process billions of records daily and led teams to achieve exceptional test coverage and minimal production bugs.
I am passionate about applying engineering discipline to AI system reliability and am actively building local LLM infrastructure on consumer hardware. This includes developing MCP bridge servers, multi-model orchestration, and empirical evaluation frameworks.
My technical skills span multiple programming languages including Java, Go, and Python, and I have extensive experience with frameworks such as Spring Boot, Axon Framework, and Apache Camel. I am proficient in cloud platforms like GCP and AWS, and I follow best practices including TDD, event modeling, and observability.
In my recent roles, I have architected and delivered complex data ingestion platforms, led cloud migrations, and introduced innovative solutions to improve system performance and reliability. I have also mentored teams in TDD and driven adoption of event-driven design patterns.
I am fluent in English and have worked remotely across Americas and Europe time zones. I am committed to continuous learning and professional development, having completed certifications and courses in microservices architecture, software design, and Aerospike technologies.
I am eager to contribute my deep technical expertise and leadership skills to challenging backend engineering roles that focus on scalable, reliable distributed systems and innovative AI infrastructure.
Owned end-to-end architecture and delivery of a high-throughput data ingestion platform for a real-time ad tech bidding system, built during an AWS-to-GCP cloud migration. Architected Aerospike data pipeline processing 3.2 billion records daily at 350,000+ writes/second. Designed chunking strategy for processing 400+ files per batch. Diagnosed and resolved connection pool exhaustion and GCP authentication issues. Reduced Datadog costs by $8,000/month. Built Go-based acceptance testing framework.
Reduced API response time from 200ms–5s to sub-150ms using Spring Boot and Spring Cloud Stream for Kafka. Developed complex SQL queries for data inconsistency detection. Introduced TDD practices and improved coding standards.
Led full technology transition from C# to Java for TaxEngine tax calculation system. Achieved 89–96% test coverage with fewer than 5 production bugs in first year. Pioneered Event Modeling and event-driven architecture adoption. Implemented distributed Oracle database as event bridge. Designed operator-configurable tax rules system.
Led account security project through full SDLC including requirements analysis, REST API specification, microservices design, code review, testing, and production rollout.
Designed and led data integration architecture for mortgage and vehicle financing platform. Implemented anti-corruption layer design. Introduced Kafka as processing layer over MQ ingestion, reducing message loss to zero. Contributed to first Brazilian bank deployment on public cloud (Azure). Established code review and led technical design discussions.
Worked on telecom Customer Management systems.
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