Erkin Qarayev
Building production-grade AI systems with multi-agent orchestration, RAG pipelines, and scalable full-stack architectures. 4+ years shipping real software at Technosec.io.
01 / About
Building intelligent systems
that solve real problems.
Software Engineer with 4+ years at Technosec.io, specializing in AI infrastructure, multi-agent orchestration, and production-grade systems. Open-source contributor to the JupyterLab ecosystem.
AI & Multi-Agent Systems
Architected a 15K LoC multi-agent orchestration platform with 14 autonomous agents, LangGraph state machines, and intelligent LLM routing.
RAG & Infrastructure
Built full RAG pipelines with document chunking, embedding generation, vector storage, and semantic search across multiple file formats.
Full-Stack Development
Next.js, React, FastAPI, and TypeScript expertise. Real-time WebSocket streaming, Zustand state management, and clean architecture.
Testing & DevOps
Comprehensive test automation with 80%+ coverage. CI/CD pipelines reducing deployment from hours to under 20 minutes.
Years Experience
AI Agents Built
Lines of Code
Test Coverage
Sprint Completion
Production Incidents Resolved
02 / Experience
Where I've been
building things.
Software Engineer
Technosec.io
- Architected multi-agent orchestration platform (~15,000 LoC) with 14 specialized AI agents using LangGraph, LangChain, and FastAPI
- Built full RAG pipeline with document chunking, Ollama embeddings, vector storage, and semantic search
- Implemented multi-provider LLM abstraction supporting Ollama, OpenAI, Anthropic Claude, and Google Gemini
- Developed persistent agent memory system with SQLite-backed pattern learning and confidence scoring
- Built conflict resolution system for multi-agent collaboration using weighted voting and consensus thresholds
- Created Next.js 16 / React 19 frontend with real-time WebSocket streaming and agent status visualization
- Built comprehensive test automation framework — 200+ E2E test cases, increasing coverage from ~40% to 80%+
- Implemented CI/CD pipelines reducing deployment time from hours to under 20 minutes
- Built custom JupyterLab extensions with TypeScript and React, reducing repetitive tasks by ~35% for 15+ data scientists
03 / Projects
What I've built.
From multi-agent AI platforms to real-time dashboards, each project represents a deep dive into solving complex engineering challenges.
Multi-Agent Orchestration Platform
~15,000 Lines of Code | 14 Autonomous Agents
Production-ready platform using LangGraph, LangChain, and FastAPI. Features agents with real autonomy — accept, refuse, question, retry, and delegate decisions with a LangGraph state-machine supervisor and intelligent LLM-based routing with rule-based fallback.
RAG Pipeline System
Semantic Search & Document Intelligence
Full retrieval-augmented generation pipeline with document chunking, Ollama embedding generation, vector storage, and semantic search — enabling agents to ground responses in uploaded documents with configurable top-K retrieval.
Real-Time Agent Dashboard
Next.js 16 / React 19 Frontend
Full-featured frontend with real-time WebSocket streaming, chat history management, file upload for RAG, and agent status visualization using Zustand state management and Recharts.
CI/CD & Test Automation
200+ E2E Tests | 80%+ Coverage
Comprehensive test automation framework using Selenium and Playwright across Chrome, Firefox, and Safari. Integrated into GitLab CI/CD with parallel execution, reducing QA cycle time from 3 days to under 4 hours.
JupyterLab Extensions
Open-Source | 90%+ Adoption
Custom JupyterLab extensions built with TypeScript and React, reducing repetitive data analysis tasks by ~35% for 15+ data scientists. Published as open-source with community code reviews.
AI-Powered Dev Workflows
Claude Code Integration | MCP Servers
AI-powered development workflows using Claude Code, orchestrating specialized agents for code review, security analysis, and automated testing with custom MCP servers, hooks, and prompt engineering strategies.
04 / Skills
Technical expertise.
From low-level infrastructure to high-level AI orchestration, a comprehensive toolkit honed through real-world production systems.
AI & LLM Orchestration
Architected a 14-agent platform with autonomous decision-making, conflict resolution, and persistent memory.
Languages & Frameworks
Full-stack development with Python and TypeScript, building real-time dashboards and FastAPI backends.
Testing & Quality
Built 200+ E2E tests with 80%+ coverage, reducing QA cycles from 3 days to under 4 hours.
DevOps & Infrastructure
CI/CD pipelines reducing deployment from hours to minutes, with parallel execution and Docker containerization.
Learning journey
Key milestones in my growth as an engineer.
Joined Technosec.io as Software Engineer
Started building production web apps and test infrastructure.
Scaled test automation to 200+ E2E tests
Achieved 80%+ coverage across Chrome, Firefox, and Safari.
JupyterLab extensions adopted by 90%+ team
Open-source React/TypeScript plugins reducing repetitive tasks by 35%.
Architected multi-agent AI platform
14 autonomous agents, 15K LoC, LangGraph state machines.
AI-powered dev workflows with Claude & MCP
Integrating AI into CI/CD lifecycle with custom MCP servers and hooks.
05 / Contact
Let's build something
extraordinary.
I'm always interested in discussing new opportunities, AI architecture challenges, or innovative engineering problems.