6,786 contributions last 12 months
- Python 57.4%
- Go 20.4%
- TypeScript 18.4%
- HTML 0.7%
- JavaScript 0.7%
- Kotlin 0.7%
- C# 0.6%
- Shell 0.4%
FILE / 001
Portfolio
Hello, I'm Aleksandr
AI Product Manager and hands-on LLM engineer — RAG, agent orchestration, and the Python behind them
Open to Connect
While I'm currently not actively seeking new opportunities, I'm always open to connect and discuss potential collaborations or professional advice. Feel free to reach out for any inquiries.
02
/ SKILLS
The craft, earned.
01
SKILLS
Artificial Intelligence
LLM engineering across retrieval-augmented generation with vector and hybrid search, agent and retrieval orchestration on LangChain and LangGraph, Model Context Protocol tooling, LangSmith observability, and evaluation-driven delivery of production AI systems.
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02
SKILLS
Model Context Protocol
MCP end to end — servers published to PyPI and the official registry, clients wired into agent runtimes across four transports, an authenticated gateway in front of internal servers, and protocol-level defects reported upstream, one of them already fixed and released.
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03
SKILLS
Python
Production Python for AI systems — async FastAPI and FastMCP services, LangChain and LangGraph retrieval pipelines, tested with pytest and shipped through automated release and deployment pipelines.
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04
SKILLS
Claude Code
Professional-grade command of Claude Code — orchestrators, subagents, dynamic workflows, hooks, skills, slash commands, MCP, and context engineering — applied to production multi-agent development environments.
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05
SKILLS
AI Product Management
Expertise in developing and launching AI-powered products, combining strategic vision with Agile practices and robust market and user analytics.
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06
SKILLS
Databases
Relational database design and SQL, plus hands-on work with the SQLite, PostgreSQL, MongoDB, and Chroma stores behind AI retrieval systems I build — pgvector and sqlite-vec, full-text, semantic, and hybrid search.
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03
/ GITHUB
The work, in public.
04
/ EXPERIENCE
Where the work lived.
Feb 2025
—
Present
AI Product Manager
Spotware Systems
Driving innovation and delivering strategic AI solutions at Spotware Systems across product management, AI enablement, and agentic workflows.
Full-time
Limassol, Cyprus
Apr 2024
—
Feb 2025
Business Analyst and Scrum Master
Spotware Systems
Leading business analysis and Scrum implementation at Spotware Systems, enhancing product development and team performance through detailed requirements gathering and Agile practices.
Full-time
Limassol, Cyprus
05
/ PROJECTS
Projects, released.
01
PROJECTS
AEGIS
An opinionated, hardened Claude Code environment that extends the harness rather than replacing it: curated skills, always-on rules, quality-enforcing hooks, MCP servers, durable cross-session memory, and a quality toolchain, with deliberate model, effort, and permission defaults. It rides on Claude Code's native dynamic-workflow orchestration and supplies the reliability and standards layer around it. Installable via Claude Code Toolbox, backed by MCP Context Server, with quality gates enforced at runtime.
In Development
Sep 2025 —
Present
02
PROJECTS
MCP Context Server
A high-performance Model Context Protocol server that gives LLM agents a durable, searchable memory layer beyond the context window. Thread-scoped storage over SQLite or PostgreSQL, with semantic, full-text, and hybrid search, cross-encoder reranking, pluggable embedding and summary providers, metadata filtering, and batch operations — all behind a standard MCP interface.
Active
Sep 2025 —
Present
03
PROJECTS
Claude Code Toolbox
A cross-platform installer and declarative environment-configuration framework for Claude Code. One YAML file captures all agents, MCP servers, slash commands, hooks, skills, rules, system prompts, and settings; one command installs everything on Windows, macOS, or Linux — portable, reproducible, centrally updatable.
Active
Aug 2025 —
Present
04
PROJECTS
CXR Draft Auditor
A research and educational quality-assurance tool that gives a chest X-ray draft impression a transparent second read. Two tiny 4B models — a fine-tuned MedGemma that grounds the image into labeled findings with bounding boxes and an NVIDIA Nemotron-3 Nano 4B that parses the draft into the same labels — feed a deterministic, model-free comparator that flags MISSING, UNSUPPORTED, and URGENT discrepancies, with every flag traced to a specific finding, a specific phrase, and a box on the image. Not a medical device and not a diagnostic tool.
Active
Jun 2026 —
Present
06
/ CERTIFICATIONS
The papers, stamped.
01
CERT
Build Small Hackathon 2026
Certificate of participation in Build Small, a Hugging Face × Gradio hackathon celebrating small, local, open-weight models — building real, tinkerable apps powered entirely by models under 32B parameters.
Hugging Face
Jun 2026
02
CERT
Professional Scrum Master I (PSM I)
The certification validates my knowledge of the Scrum framework, the Scrum Master accountabilities and how to apply Scrum.
Scrum.org
Feb 2023
03
CERT
Develop Your Skills as a Software Project Manager
A validation of acquiring in-depth knowledge and practical skills in managing software projects, focusing on Agile and Scrum methodologies, risk assessment, team collaboration, and effective communication.
LinkedIn Learning
Dec 2023
04
CERT
Atlassian Agile Project Management Professional Certificate
A comprehensive certification validating expertise in Agile project management principles and proficiency in Atlassian tools for effective project execution.
LinkedIn Learning and Atlassian
Jan 2024
07
/
LATEST POSTS
Notes, in long form.
Dynamic Workflows: When the Agent Writes Its Own Harness
For a few weeks now, Claude Code has been writing its own multi-agent harness for each task -- and it quietly retired the orchestration code I used to maintain by hand. Here is what changed, the patterns worth knowing, and the research idea I think sits underneath it.
Field Notes: Building a Chest X-ray Draft Auditor with Two Tiny 4B Models — MedGemma and NVIDIA Nemotron
A Field Notes write-up on building a chest X-ray draft auditor from open data alone: two tiny 4B models, a deterministic comparator, and the evaluation-integrity lesson that nearly cost me the better model.
MCP Context Server: Persistent Memory for Your AI Coding Agents
Your AI coding agent loses its plan every time the context window compacts. MCP Context Server fixes that with persistent, searchable memory -- one Docker command and your agents remember everything.
Simplifying BPMN: A Beginner's Guide to Process Modeling in Software Development
This guide breaks down the BPMN standard, highlighting key elements and their application in software development projects, with practical examples and resource recommendations.