I build systems that scale. From distributed file systems handling 10K+ files to ML models with 97% accuracy, I focus on creating robust, production-ready solutions.
My approach: Design for failure, optimize for performance, and ship with confidence.
func BuildSomethingAwesome() {
for challenge := range problems {
solution := Solve(challenge)
Deploy(solution)
}
}Teams were exceeding log volume budgets without visibility into costs, leading to unpredictable infrastructure expenses.
Custom Kubernetes operator with policy enforcement, real-time budget tracking, and self-service cost management dashboard.
┌─────────┐ ┌──────────┐ ┌─────────┐ │ K8s CRD │───▶│ Operator │───▶│ Metrics │ └─────────┘ └──────────┘ └─────────┘
Building a distributed file system that handles concurrent access, ensures data consistency, and scales horizontally.
Implemented consistent hashing for data distribution, write-ahead logging for durability, and S3 as the storage backend.
Client ──▶ Load Balancer ──▶ Node Pool
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AWS S3 (Storage)
Detecting fake reviews in real-time with high accuracy while maintaining low latency for browser extension users.
BI-LSTM model trained on 50K+ reviews, containerized API with auto-scaling, and lightweight Chrome extension with local caching.
Extension ──▶ API Gateway ──▶ ECS Tasks
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ML Model (97%)
Tax forms are complex and intimidating, leading to high abandonment rates and user frustration.
Progressive disclosure UI, real-time validation, auto-save functionality, and guided workflows that increased completion by 40%.
Next.js App ──▶ API Routes ──▶ DynamoDB
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Auth (Secure)