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Achievement: StarstruckAchievement: Pair ExtraordinaireAchievement: YOLOAchievement: Arctic Code Vault ContributorAchievement: Pull Sharkx3

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akrisanov/README.md

Staff Software Engineer building AI infrastructure and distributed systems.

Most recently at Severstal, I worked on a production GenAI platform running on Kubernetes and NVIDIA GPUs across multiple data centers. My work covered LLM serving, routing, GPU placement, capacity planning, reliability, observability, model rollouts, and performance tuning.

I prefer roles where I can design systems, write code, investigate production issues, and own technical decisions end to end.

Earlier in my career, I built backend and platform systems across SaaS, fintech, payments, data privacy, and high-traffic products.

I write about AI infrastructure, ML systems, and distributed systems at akrisanov.com.

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  1. plans plans Public

    Portable, harness-agnostic planning and coordination for agent-driven software work.

    Python 2

  2. kubetask kubetask Public

    Kubernetes-based execution service for isolated, short-lived tasks with resource controls, artifact storage, and task lifecycle management.

    Go 1

  3. local-agent-stack local-agent-stack Public

    Local-first stack for running coding agents against shared local or remote inference.

    Python 2

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

    vLLM serving environment with GPU provisioning, workload telemetry, ClickHouse analytics, and Grafana observability.

    Python

  5. python-field-notes python-field-notes Public

    🐍 Practical examples, experiments, and reference notes for modern Python.

    Jupyter Notebook 6

  6. planfact/Reliable.HttpClient planfact/Reliable.HttpClient Public

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

    C# 9