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akrisanov/README.md

Hi, I'm Andrey

I'm a software engineer with a strong background in backend platforms, distributed systems, and cloud infrastructure.

After 15+ years in engineering, including several years as CTO of a profitable SaaS company, I'm now focused on building real-world, production-ready AI features and systems. My work centers around retrieval-augmented generation (RAG), LLM-driven product capabilities, and the backend components that make these systems reliable, observable, and scalable.

I'm especially interested in the engineering side of applied AI:

  • designing RAG architectures and ingestion pipelines
  • building LLM-based services and multistep workflows
  • integrating vector databases and hybrid retrieval
  • establishing evaluation, monitoring, and safety mechanisms
  • connecting AI systems with existing backend platforms

My goal is to bridge modern AI with solid engineering, delivering AI features that are not just impressive in demos, but robust, predictable, and valuable in real products.

Get in touch

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  1. Reliable.HttpClient Reliable.HttpClient Public

    Production-ready HttpClient ecosystem: resilience patterns + intelligent caching + universal response handlers. Zero config, multiple approaches, seamless substitution.

    C# 10

  2. docstring-verifier docstring-verifier Public

    Educational project: A VS Code plug-in that looks for discrepancies between doc strings and actual implementations. If there is a mismatch, then the doc string is highlighted as an error.

    TypeScript

  3. golang_faq_ru golang_faq_ru Public

    Неофициальный перевод FAQ языка программирования Go на русский язык

    23 2

  4. llm-serving-lab llm-serving-lab Public

    Experiments with LLM serving (vLLM baselines, loadgen, metrics → ClickHouse + Grafana)

    Python

  5. http-api-design http-api-design Public

    🤌🏻 Руководство по дизайну HTTP API сервисов

    10

  6. inference-engineering-journey inference-engineering-journey Public

    A personal journey into model inference engineering — learning, building, and sharing along the way.

    Jupyter Notebook 2