AVAILABLE FOR HIRE

AI &

Full-Stack

Tech Lead

I specialize in building complex IT ecosystems, deep process automation, and AI adoption (RAG, Agents). I speed up time-to-market through AI-assisted development and high-quality refactoring.

Projects Download CV

React / Next.js

Python (Django)

PostgreSQL

Model Context Protocol (MCP)

Cursor / Claude Code

n8n Workflow

Docker

React / Next.js

Python (Django)

PostgreSQL

Model Context Protocol (MCP)

Core competencies

Full-stack expertise, product mindset, and leadership. I design systems that reduce costs, accelerate delivery, and improve process quality.

Full-Stack Architecture

Building complex web apps from scratch. TypeScript domain modeling, SSR/ISR for SEO, optimized databases.

Frontend

Next.js, React, Tailwind

Backend

Python/Django, Node.js

Data

PostgreSQL, Redis

Core Focus

AI Integrations & MCP

Integrating LLMs (GPT-4, Claude) into business processes. Designing smart tools via Model Context Protocol.

MCP Architecture

Host (AI)

MCP Server

↳call_tool("query_db")

↳read_resource("api/docs")

Capabilities

RAG pipelines & vector search

Tool use & function calling

AI guardrails & security

Automation

Process orchestration with n8n and Python scripts. Connecting CRM, messengers, databases, and generating legal/technical documentation.

WebhooksCron JobsData Parsing

cursor_agent.py — MCP Workflow

import mcp_server

from ai_engine import CursorAgent

# Connect internal tools securely via MCP

client = mcp_server.connect(transport="stdio")

async def refactor_codebase(context):

plan = await client.tools.call(

"analyze_dependencies",

{ "path": "./src/legacy" }

)

return CursorAgent.apply_diff(plan)

➜ Terminal _

MODERN ENGINEERING

AI-Native development

I don't just write code; I orchestrate development with AI agents. I use Cursor, Claude, and Gemini CLI to speed up routine tasks, refactoring, and test writing.

MCP Standards: Connect databases and APIs as tools for LLMs directly in the IDE.
Rapid Prototyping: From idea to working prototype in hours, not days.
Quality Control: AI code reviews and automatic unit test generation.

Selected projects

Real-world cases: from problem to production.

MVP Platform2025

MVP platform ShalomIsrael.ru

Task:Unify fragmented services into a single product with a reliable architecture.

Solution:Designed an MVP with PostgreSQL and API integrations, built the ecosystem from scratch.

Next.jsDjangoPostgreSQLAI Tools

-50% SDLC

100% Data Integrity

Enterprise Ecosystem2023–2025

Expertsmet.ru: website + CRM + contractor control

Task:Cover the full business loop and reduce manual operations in documents.

Solution:Built an ecosystem with an AI agent for procedures, automated quality control and HR onboarding.

Pythonn8nLLM AgentsCRM

+40% Documents

-50% Onboarding

Performance & SEO2020–2022

Freelance: high-load interfaces and SEO

Task:Boost interface speed and automate content growth.

Solution:Built fast frontends, introduced SEO infrastructure, and automated publishing.

ReactPerformanceSEO Automation

90+ Lighthouse

Growth Organic

Questions and format

Do you work as an engineer or a product manager?

I combine both roles. As a product-minded engineer, I don't just close tickets; I think about metrics and users. I take ownership of technical delivery end-to-end.

What is MCP and why does my project need it?

Model Context Protocol (MCP) is a standard for connecting data to AI. It lets you securely integrate your databases and APIs with LLMs (ChatGPT/Claude), avoiding hallucinations and creating real assistants for business.

How is data security handled when working with AI?

I use enterprise approaches: local data processing where possible, PII anonymization before API calls, strict guardrails for model responses, and secure access keys.

Ready to strengthen the team
with technical expertise?

Open to Senior / Tech Lead roles. Available for consulting on AI adoption.