I help founders and small teams turn fast-shipped, AI-generated systems into software that's actually secure, reliable, and ready for real users.
AI gets you to a working prototype fast. These are the gaps that show up once real people start using it.
AI-generated code works, but often leaves authentication gaps, exposed data, and missing input checks that real users — or attackers — will eventually find.
Getting code live safely, with proper secrets management, automated updates, and a rollback plan if something goes wrong. AI builds the app. It doesn't build the system around it.
What happens when an external service fails, a database slows down, or a user does something unexpected? AI rarely handles those cases. Production systems have to.
AI picks the simplest infrastructure, not the right one. Hosting bills compound quietly in the background until they become a line item you can't ignore.
Without proper monitoring, you find out something broke when a user tells you. That's the wrong way to find out.
Some bugs need a human who can read across the whole system, understand what's actually happening, and make a judgment call. That's what I'm here for.
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Reviewing and redesigning systems for scalability, reliability, and maintainability. Experienced in identifying architectural debt in AI-generated codebases and creating pragmatic improvement roadmaps.
Hardening AI-built prototypes for real-world usage: security gaps, error handling, observability, rate limiting, and deployment practices that production actually demands.
Designing and auditing AWS infrastructure to eliminate waste and scale efficiently. Serverless, containers, managed services — matching the right tool to the actual workload, not the AI's default choice.
Finding and fixing the database and caching issues that AI tools consistently get wrong: missing indexes, N+1 queries, wrong consistency models, no cache invalidation strategy.
Setting up the deployment pipelines, monitoring, alerting, and logging that teams skip during the AI-assisted build phase — and that you'll desperately wish you had when things break.
Auditing and hardening API contracts, authentication flows, and third-party integrations. AI-generated integrations often work until they don't — retries, timeouts, and failure modes are rarely handled correctly.
CiiRUS Inc.
United States
Led architecture and development of a large-scale SaaS platform for vacation rental management. Focused on performance, scalability, and UI modernization, transforming a legacy desktop product into a modern cloud-based solution.
KPMG Crimsonwing
Malta
Designed and developed a scalable e-learning system used by KPMG employees worldwide. Built integrations with third-party systems, optimized communication between modules, and customized functionality based on business needs using agile processes.
Itaú Unibanco
São Paulo, Brazil
Implemented IT solutions to enhance efficiency and productivity. Built system health monitoring tools reducing incidents by 60%, and developed integrations across systems to enable proactive support operations.
Bradesco
São Paulo, Brazil
Developed software to consolidate department data previously stored in hundreds of spreadsheets, improving reporting and decision-making efficiency.Built multi-threaded batch engines to synchronize large datasets across departments.
Focused on system architecture, scalability, and software design patterns. Explored distributed systems, quality assurance, and best practices for enterprise development.
Studied software development methodologies, database design, and web application programming. Gained practical experience building data-driven business applications.
AWS Certified Solutions Architect – Associate. Microsoft Certified Solutions Associate (MCSA) and Developer (MCSD). Certified Technology Specialist (MCTS) in SQL Server.