Арсеній

ARSENIY SIERIKOV
PYTHON AI ENGINEER
[відкрити контакти](див. вище в блоці «контактна інформація»)
ABOUT ME
[відкрити контакти](див. вище в блоці «контактна інформація») I’m a Python AI Engineer focused on LLM features and RAG for

@boyzfromthehood8
chat assistants. I build backend services and RAG pipelines
(document ingestion, chunking, embeddings, relevant context
[відкрити контакти](див. вище в блоці «контактна інформація») retrieval) and integrate the OpenAI API. I’ve worked in a small team
arseniy-serikov-0912ba3a1/ on projects and prototypes, delivering key AI and backend modules
from requirements to a working MVP. I also developed Telegram
bots and Telegram sales bots (product catalog, orders, basic
SKILLS automation). I use FastAPI and PostgreSQL; I’m familiar with
Docker and Git and have used them for local environments and
Python version control.
Java Script
Flask, FastAPI, Django, REST API
Telegram Bots
OpenAI API integration
EXPERIENCE
SQL (PostgreSQL)
Docker (fundamentals) PYTHON AI ENGINEER
Machine and Deep Learning
PROJECT EXPERIENCE (LLM/RAG/BACKEND)
fundamentals
2022 - Present | Project-based / Team projects
Large Language Models (LLM)
Retrieval-Augmented Generation Built Python backend services with FastAPI/Flask: REST
(RAG) basics APIs, data validation, error handling, and modular
Business Process Modeling (BPMN, architecture.
IDEF0 end other) Implemented a RAG pipeline for document-based Q&A: file
ingestion, chunking, embeddings, relevant context retrieval,
and context formatting for generation.
Integrated OpenAI API for text generation and/or
EDUCATION embeddings in chat-assistant workflows.
Developed Telegram bots for sales and user interaction:
National Technical University “Kharkiv
commands, message handling, product catalog/orders,
Polytechnic Institute”
Bachelor’s Degree in Intelligent
notifications, and basic automation.
Systems and Computer Science Worked with SQL databases (PostgreSQL/MySQL): schema
Department of Computer Science design, relationships, queries, and application data
2022 – 2026 (expected) persistence.
Collaborated in a small team: requirements clarification, task
LANGUAGE breakdown, module integration, and delivery to a working
MVP/prototype.
English Used Docker and Git in practice for local environments and
version control.