Senior Software Engineer building high-scale .NET platforms, event-driven systems, and developer-first APIs.

I work on distributed systems, platform migrations, performance bottlenecks, and AI-enabled product features. Most of my production work lives in private enterprise codebases, so this profile is where I keep public experiments, tooling, and notes around the same engineering problems.

• Modernizing legacy .NET systems into containerized, Linux-based, CI/CD-driven platforms.
• Designing event-driven workflows with Kafka, MassTransit, background workers, and multi-tenant services.
• Building and tuning GraphQL APIs, especially around N+1 query patterns and DataLoader strategies.
• Migrating persistence layers across SQL Server, PostgreSQL, EF Core, Dapper, and database-first architectures.
• Integrating LLM and ML capabilities into existing product surfaces without overcomplicating the core system.

• Reworked a failing saga flow into an event-driven architecture, moving a critical provisioning path from a 99% failure rate under concurrent load to reliable execution for thousands of concurrent requests.
• Helped migrate 500+ customer-specific service instances into a multi-tenant clustered architecture with demand-based scaling.
• Built migration automation that removed roughly 95% of manual comparison and merging work during platform adoption.
• Reduced GraphQL permission-layer latency by about 70% by redesigning the DataLoader strategy.
• Led a .NET Framework 4.7.2 to .NET 9 modernization, including Docker, Linux hosting, PostgreSQL, EF Core, Hangfire, and ASP.NET Identity.
• Reduced monthly infrastructure cost by about 90% through rightsizing and platform modernization.
• Re-engineered a CRM data ingestion pipeline for 300k+ record CSV imports, cutting processing time from over 5 minutes to about 40 seconds.

Languages:       C#, JavaScript, SQL
Backend:         .NET, ASP.NET Core, MVC, Hosted Services, Hangfire
Data:            PostgreSQL, SQL Server, EF Core, Dapper
Architecture:    Kafka, MassTransit, GraphQL, microservices, multi-tenant systems
Infrastructure:  Docker, Linux, Windows Server, IIS, CI/CD, AWS
Frontend:        React, JavaScript, jQuery
AI:              LLM integration, RAG systems, ML-assisted product features

• Cleaner modernization paths for legacy enterprise systems.
• Practical AI integrations that fit real product constraints.
• Better developer workflows for migration, comparison, and verification work.
• Distributed-system reliability under concurrency, retries, and partial failure.

• LinkedIn: linkedin.com/in/gabrielbels
• GitHub: github.com/GabrielBels