The world of technology and software architectures has always been fascinating to me. I’ve consistently tried to stay up-to-date in this field and have pursued relevant studies to grow and enhance my skills. Creativity, persistence, commitment, and a strong sense of responsibility are among my key soft skills in this area.
Recently, my focus has expanded into AI-powered software: integrating large language models (LLMs) into enterprise products, building RAG-based assistants, and adopting AI-assisted development workflows to boost team productivity.
During my work experience, I have become familiar with various tools and technologies, which are listed below. (This does not imply full mastery of all of them.)
Language and Framework: C#, .NET, ASP.NET Core, .NET CLI, ASP.NET Framework, ASP.NET
WebForms, Blazor, ABP
AI & LLM: Semantic Kernel, Microsoft.Extensions.AI, OpenAI / Azure OpenAI APIs, Claude API,
RAG (Retrieval-Augmented Generation), Prompt Engineering, Function Calling, MCP (Model Context Protocol)
Vector Search & Embeddings: Qdrant, pgvector, Redis Vector Search
AI-Assisted Development: GitHub Copilot, Claude Code, Cursor, AI code review & agentic workflows
ORM: EntityFramework, Dapper
Version Control: Git, Tfs, Github, Gitlab, Azure DevOps, BitBucket
OOP: SOLID, DRY, KISS
Architecture & Style: DDD, Clean, Monolith, Microservice
Database: MS-SQL, Oracle, Postgres, MongoDB, Redis
Service Communication: REST API, Minimal API, SOAP, gRPC, SignalR
Task Scheduling: Quartz, Hangfire
Mobile: MAUI Hybrid
Message Broker: ActiveMQ, RabbitMQ
API Gateway: YARP, Ocelot, Kong
Libraries: Polly, FluentValidation, MediatR
FileStorage: MinIO
Testing: Unit Testing, E2E (Cypress)
Caching: Redis, Memcached
Logging & Observability: Serilog, ELK, Grafana, Prometheus, OpenTelemetry, Jaeger
DevOps: Docker, Podman, Kubernetes (K8s), Azure Pipelines, GitHub Actions