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Sauryk Tassybayev

@Saur

ML/AI Backend Engineer

Applied AI/ML Engineer focused on LLM applications, AI agents, RAG systems, and backend development.

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About

Experienced in building production-ready AI solutions with FastAPI, PostgreSQL, vector databases, and modern LLM frameworks. Passionate about practical AI applications and continuous learning.

Career

Experience: 3 years

Experience

AI Engineer

Astana Hub

Kazakhstan innovation hub and startup ecosystem.

Feb 2026 — Present

Built enterprise LLM, RAG, document-processing, and semantic-search systems; reduced API latency by up to 50%.

• Designed and implemented enterprise AI systems based on LLMs, RAG, hybrid retrieval, and agentic workflows. • Built AI-powered document validation and document processing pipelines (PDF, DOCX, OCR). • Developed semantic search services using Qdrant and embedding-based retrieval. • Integrated LLMs with Telegram Bots, NocoDB, n8n, and enterprise REST APIs. • Designed retrieval pipelines for enterprise knowledge bases. • Optimized backend performance, reducing API latency by up to 50%.

Backend Engineer

Astana Hub

Kazakhstan innovation hub and startup ecosystem.

Apr 2024 — Feb 2026

Developed Python backend services and APIs serving systems with up to 30,000+ MAU; improved latency and database load.

• Developed and enhanced backend services in Python (Django, DRF). • Developed and automated corporate business processes. • Designed REST APIs for systems with active user load of up to 30,000+ MAU. • Optimized SQL queries and business logic, reducing API latency by approximately 30–50%. • Reduced N+1 queries and optimized ORM queries, reducing database load by up to 40%. • Participated in architectural decisions and code reviews, improving release stability.

Research Assistant

OmnAI Lab

Mar 2022 — Jul 2022

Researched and evaluated machine-learning models, prepared datasets, and contributed to technical reports and research publications.

• Conducted research in machine learning, deep learning, and generative AI. • Developed, trained, and comparatively analyzed machine learning models using PyTorch and Scikit-learn. • Preprocessed, analyzed, and prepared research datasets for model training. • Conducted experiments, selected hyperparameters, and compared models. • Assessed model quality using Accuracy, Precision, Recall, F1-score, and ROC-AUC. • Prepared technical reports and contributed to research publications.

Education

B.Sc., Information Engineering (Artificial Intelligence & Computer Science)

Sapienza University of Rome

2023

B. Engineering, Transport Management

Taraz State University

2014

Selected projects

AION – AI Agent Platform for Workflow Automation

Multi-agent enterprise AI platform for workflow automation and intelligent task execution. Designed and developed using LangGraph, OpenAI models, and FastAPI; includes tool calling, memory management, multi-step reasoning, Qdrant retrieval, backend orchestration, and a foundation for integrations with Telegram, Slack, Jira, GitHub, and productivity tools.

AIDA Platform — AI-Powered Knowledge & Decision Support System

Built a RAG-based semantic search and knowledge retrieval system, data-ingestion pipelines for structured and unstructured data, LLM-powered Q&A and analysis, and backend APIs.

AI HR Assistant

Developed an LLM- and RAG-powered KPI validation assistant with document analysis and automated report verification, integrating Telegram Mini Apps, FastAPI, and OpenAI models.

Skills

AIMLBackedDS