3rdkosme

Consolidated a legacy voicemail-to-email service into the core PBX system by migrating 500K+ configuration records. Designed and implemented parallel writes, fallback reads, and Redis-based idempotency to ensure safe synchronization across multiple consumers and prevent duplicate email deliveries. Architected background processing infrastructure using Quartz.NET to offload heavy synchronous operations. Identified and eliminated a N+1 query bottleneck, reducing data propagation time from up to ~2 minutes to ~20ms for large customers. Optimized application observability and log management. Reduced logging noise by filtering entries from ~100 down to 5-10 high-value logs per request in Splunk, which significantly accelerated incident debugging and reduced log storage costs. Managed AWS infrastructure components for backend services using ECS and AWS Secrets Manager. Provisioned isolated EKS pods to safely test global configuration changes and deployments prior to production releases. Regularly participated in code reviews and technical discussions, identifying potential bugs, performance issues, and architectural concerns before merging changes. Integrated Claude into CI/CD pipelines for automated Pull Request reviews. Configured project-specific review rules, improving code consistency and significantly reducing manual review effort. Project Tech Stack: C#, .NET, Kafka, Redis, MySQL, MongoDB, Quartz.NET, AWS, EKS, Splunk, Grafana.

Architected event-driven workflows utilizing Kafka for service decoupling. Successfully implemented asynchronous pipelines for AI-based image processing and broadcast mechanisms for automated order distribution workflows, improving platform scalability. Integrated third-party AI services into a unified backend architecture. Designed and exposed REST APIs to support business logic, including intelligent matching algorithms, recommendation pipelines, and interactive social features. Optimized data access and overall system performance by designing scalable MySQL schemas (via Entity Framework Core/Dapper) and implementing Redis caching strategies. This approach reduced latency for read-heavy operations like recommendation generation and user feeds. Project Tech Stack: C#, ASP.NET Core, Kafka, Redis, MySQL, Entity Framework Core, Dapper, Docker, xUnit, Moq.