Cloud Infrastructure & AI Solutions Engineer
I design scalable backend architectures, orchestrate automated deployment pipelines, and integrate autonomous multi-agent AI workflows into production environments. Focused on high system availability, containerization, and monitoring.

• Infrastructure & DevOps: Docker, CI/CD (GitHub Actions), Linux Shell Scripting (Bash), Cloud Deployment (Render, Vercel), Infrastructure Monitoring (UptimeRobot, Grafana)
• Backend & AI Orchestration: Python, FastAPI, Aiogram (v3), CrewAI, LangChain, Multi-Agent Systems, Advanced Prompt Engineering
• Databases & Storage: PostgreSQL, Redis, Automated Backup Systems
• Frontend Integration: React (Vite), TailwindCSS, Asynchronous API Binding

Autonomous web content analysis and asynchronous code review infrastructure driven by multi-agent frameworks.
🔗 Core Stack: CrewAI, LangChain, OpenAI API, Python.

• Architecture & Orchestration: Designed an autonomous multi-agent ecosystem optimized for parallel processing of technical SEO audits and code quality validation.
• Custom Tooling: Developed specialized sandboxed tools (Read URL Content) and custom skill sets (SEO-Expert) to maximize agent execution autonomy.
• Tracing & Debugging: Integrated advanced orchestration tracing to monitor agent reasoning paths, token consumption, and system execution states in real-time.

Production-ready infrastructure featuring an asynchronous backend and automated data analysis architecture powered by LLMs.
🔒 Note: Repositories are private due to proprietary architecture and secure API token management.

• Backend & Pipeline Architecture: Developed a high-performance, asynchronous Python backend using FastAPI to handle high-concurrency requests and aggregate complex live gaming metrics...
• Deployment & Resilience: Containerized the entire application environment using Docker. Implemented automated daily database backup workflows and integrated persistent monitoring to ensure maximum uptime.
• Secure Authentication Integration: Established third-party authentication flows via the OpenID protocol (Steam Auth) for secure, passwordless user identification.
• AI Analytics Engine: Engineered prompt structures and system routines with the Groq API to transform unstructured statistical tables into clean, deterministic data insights.

High-throughput, asynchronous AI-powered microservice for text parsing and rapid credibility analysis.

• High-Concurrency Architecture: Built on top of the aiogram framework with an asynchronous event loop, allowing the system to process hundreds of concurrent user requests smoothly without pipeline bottlenecks.
• LLM Gateway Integration: Configured zero-latency streaming pipelines with the Llama 3 neural network utilizing Groq's high-speed hardware acceleration API.
• Analytical Prompt Engineering: Designed rigorous multi-layered system instructions enabling the AI engine to systematically break down text using structured criteria (logical fallacies, clickbait detection, source reliability markers).

Full-cycle decentralized infrastructure framework for executing contract interactions and managing token minting flows.
🔗 GitHub Repository: WEB3-Token-Minting-dApp

• Smart Contract Deployment: Engineered and deployed secure ERC-20 token smart contracts onto testnet environments utilizing Solidity, managing automated incoming execution state logic.
• Web3 State Binding: Configured asynchronous state management hooks using RainbowKit, Wagmi, and Viem to bind frontend clients with active blockchain ledger providers.