VB
Victor Buzin

Hi, I'm Victor Buzin

From junior developer to engineering leader at Fortune 500 companies. 16 years building enterprise systems, leading international teams, and now pioneering AI-powered solutions.

Full CV
Victor Buzin - Head of Software Development and AI Engineer

My Journey

16 years of turning ambition into impact — from writing first lines of code to leading engineering at a European energy giant

Victor Buzin - Head of Software Development and AI Engineer

I started my career as a junior .NET developer in Saint Petersburg, driven by curiosity and a passion for building things that matter. Over the years, I've grown through every stage — from hands-on coding at Heineken and architecting solutions at Veeam Software, to leading engineering teams for global clients like Daimler, L'Oréal, and ThyssenKrupp. Today, as Head of Software Development at SEFE (formerly Gazprom Germania) in Berlin, I lead a 12+ person international team delivering mission-critical enterprise applications for one of Europe's largest energy companies.

What sets me apart is the rare combination of deep technical expertise and proven leadership. I've built 3 engineering teams from scratch, mentored 5+ developers into senior roles, and consistently delivered 25%+ efficiency gains. Now I'm combining my enterprise architecture background with AI — building intelligent automation workflows, LLM orchestration systems, and RAG pipelines that transform how businesses operate.

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Years in Tech
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Enterprise Apps
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Team Built To
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Engineers Mentored

Technology Stack

Battle-tested tools powering enterprise solutions from code to cloud to AI

Backend & Languages

C#.NET CoreASP.NET CoreGoTypeScriptEntity FrameworkDappergRPC

AI & Automation

Semantic KernelRAG PipelinesLLM Orchestrationn8nFlowiseAI PipelinesLangchain

Frontend

ReactNext.jsVue.jsBlazorTypeScriptTailwind CSSAngular

Databases

PostgreSQLSQL ServerRedisElasticsearchELK Stack

Cloud & DevOps

AzureDockerKubernetesCI/CDAzure DevOpsSerilogAPM

Architecture

Clean ArchitectureDDDCQRSMicroservicesModular MonolithSOLIDEvent-Driven

Messaging & Integration

Apache KafkaRabbitMQHangfireRESTful APIsSalesforceOffice 365

Leadership

Team BuildingAgile/ScrumMentoringStrategic PlanningRelease ManagementCode Review

Open Source & Projects

Public tools, experiments, and open-source contributions

Delibera screenshot 1

Delibera

Thoughtful AI Decisions — a .NET 10 framework for collective decision-making through structured multi-model deliberation. Councils, Chairman, RAG (Qdrant / pgvector), MCP tools, and context compression.

C#.NET 10AI AgentsRAGQdrantpgvectorOpen SourceLLM Council
Hercules screenshot 1

Hercules

A compact self-improving micro-agent on C# / .NET 10. Creates skills from experience, improves them during use, and retains knowledge across sessions. YandexGPT, Ollama Cloud, and Ollama Local through one OpenAI-compatible interface.

C#.NET 10AI AgentsSelf-ImprovingYandexGPTOllamaExperimentalOpen Source
Marp Play screenshot 1

Marp Play

Free online Markdown presentation viewer and player. Paste your Marp-flavored Markdown and instantly preview beautiful slides — no install required.

MarpMarkdownPresentationsOpen SourceTypeScript

Latest Articles

Thoughts on software engineering, architecture, and the .NET ecosystem

View All Articles
RAG Evaluation Before Production: A Practical Guide
2026-08-0415 min read

RAG Evaluation Before Production: A Practical Guide

A RAG system without a maintained evaluation dataset is a system that cannot be improved or safely changed. A practical guide to the Minimum Viable Evaluation Dataset (MVED), the five essential categories, LLM-as-Judge architectures, and connecting evaluation to deployment gates.

AIArchitectureLLM
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Chunking Is Not a Strategy: How to Choose Retrieval Units
2026-08-0110 min read

Chunking Is Not a Strategy: How to Choose Retrieval Units

The choice of retrieval unit is the most consequential design decision in a RAG pipeline. Why character splitting fails, the precision/recall trade-off, parent-child and hierarchical patterns, the lost-in-the-middle constraint, and a unit-selection table.

AIArchitectureLLM
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From Senior Engineer to Principal: What Changes and What Does Not
2026-07-2912 min read

From Senior Engineer to Principal: What Changes and What Does Not

The jump from Senior to Principal is not a linear climb — it's a career pivot. A field note on impact radius, problem sourcing, ambiguity, and the day-to-day reality of moving from individual execution to organizational leverage.

CareerLeadershipEngineering Management
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RAG Is a System, Not a Prompt: Retrieval, Context, Evaluation and Operations
2026-07-2622 min read

RAG Is a System, Not a Prompt: Retrieval, Context, Evaluation and Operations

RAG answer quality is determined at four separate stages — Retrieval, Context, Answer, Operations — each testable independently. A stage-by-stage framework with metrics, ten common failure modes, and a senior-engineer checklist.

AIArchitectureLLM
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5 Questions Before Starting a RAG PoC
2026-07-238 min read

5 Questions Before Starting a RAG PoC

Most RAG PoCs fail not because the technology is broken, but because the architecture was built on unexamined assumptions. Five questions every technical lead should answer before writing the first line of orchestration code — covering retrieval units, evaluation, corpus ownership, latency/cost, and failure UX.

AIArchitectureLLM
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A Practical Reference Architecture for Enterprise RAG on .NET and Azure
2026-07-2015 min read

A Practical Reference Architecture for Enterprise RAG on .NET and Azure

Enterprise RAG on .NET is a system with eight distinct decision surfaces, each with its own failure modes. A staff-level reference architecture covering ingestion, vector stores, hybrid retrieval, reranking, and observability on Azure.

AIArchitectureLLM
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From AI Demo to Production: What Enterprise Teams Actually Need
2026-07-179 min read

From AI Demo to Production: What Enterprise Teams Actually Need

A field guide for CTOs on closing the gap between a working AI demo and a governed, production-ready enterprise system — covering architecture, reliability, security, cost, and ownership.

AIArchitectureLLM
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Why 'an LLM Chatbot' Is Not an AI Architecture
2026-07-177 min read

Why 'an LLM Chatbot' Is Not an AI Architecture

An LLM call is not an architecture. A field guide for technical leads and architects on the seven non-negotiable surfaces — retrieval, evaluation, economics, ownership, and failure UX — that separate a prototype from a production system.

AIArchitectureLLM
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.NET 11: A Deep Dive into the Future of .NET
2026-04-2512 min read

.NET 11: A Deep Dive into the Future of .NET

Explore the exciting new features in .NET 11 — from runtime-native async and C# 15 to massive performance improvements and ASP.NET Core 11 enhancements.

.NETC#ASP.NET Core
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Let's Build Something Great

Whether you need a technical leader, architecture review, AI strategy consulting, or a hands-on engineering partner — I'm here to help.