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Applied AI Engineer

Рассматривает должности:
Applied AI Engineer, Python-програміст
Возраст:
19 лет
Город проживания:
Харьков
Готов работать:
Удаленно

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Kalashnyk Kyrylo

Applied AI Engineer | Multi-Agent Systems & LLM Orchestration | Live in Antalya, Turkey |
[открыть контакты](см. выше в блоке «контактная информация») | [открыть контакты](см. выше в блоке «контактная информация») (Telegram/WhatsApp)

Summary

High-performance Software Developer specializing in Agentic Workflows and autonomous AI
systems. I bridge the gap between complex engineering and practical AI applications, building
reliable RAG pipelines and multi-agent architectures that deliver measurable business results. Expert
in utilizing AI-native tools (Cursor, Claude Code) to accelerate development velocity while
maintaining high production standards.

Technical Skills

●​ AI & Orchestration: LLM Integration (OpenAI, Anthropic), Agentic Workflows,
LangGraph, Agno, RAG, Prompt Engineering.
●​ Languages: Python (Advanced), SQL, C#, JavaScript.
●​ Backend & Automation: FastAPI, Asyncio, n8n, REST APIs, Telegram Bot API.
●​ Data & Vector DBs: Qdrant, ChromaDB, PostgreSQL, JSON-based state management.
●​ DevOps & Tools: Docker, Git, Linux (Bash), Postman.
●​ Game Development: Unity (AI-driven NPC logic, C#).

Professional Experience
Applied AI Engineer (Independent Projects & Contracting) May 2023 — Present

I specialize in architecting autonomous agentic systems and advanced RAG pipelines, transforming
complex requirements into reliable, production-ready solutions with a focus on system observability
and minimizing hallucinations.

●​ Autonomous Agentic Workflows (MissionControl): Architected a hierarchical multi-agent
framework using the Manager-Worker pattern and Claude 4.6 Adaptive Thinking.
Implemented autonomous planning, tool-use orchestration, and self-correction loops to ensure
high task completion rates.
●​ Advanced RAG & Knowledge Retrieval: Developed sophisticated RAG pipelines using
GraphRAG patterns. Optimized retrieval accuracy for large unstructured datasets using
Qdrant and ChromaDB, ensuring data traceability and groundedness.
●​ Enterprise Automation & Integration: Engineered robust n8n workflows integrated with
custom Python microservices. Developed an intelligent Lead Enrichment system that
autonomously classifies business leads with 5x efficiency gains via LLM-driven analysis.
●​ Reliability & AI Observability: Implemented "LLM-as-a-judge" evaluation frameworks
to monitor agent reasoning traces. Used structured data validation with Pydantic v2 to ensure
deterministic outputs in probabilistic systems.
●​ Scalable AI Infrastructure: Developed a full-stack platform for AI image generation
(FastAPI + Stable Diffusion), optimizing performance with Asyncio and Docker for
high-concurrency environments.

Education

National Technical University "Kharkiv Polytechnic Institute" (NTU KhPI) Bachelor’s in
Software Engineering (Focus: AI and Game Development) Kharkiv, Ukraine (Remote/Hybrid) | 2025
– Present

Languages

●​ English: B2 (Upper-Intermediate)
●​ Polish: B1/B2 (Intermediate)
●​ Ukrainian / Russian: Native

Additional Information

●​ Interests: Agentic AI, Autonomous Workflows, Backend Scalability, AI-driven Game Logic.
●​ Availability: Open to Remote / Worldwide opportunities.​

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