Даніїл

Senior AI/ML ENGINEER
A I & M L E n g i n e e r w i t h 4 + y e a r s o f c o m m e r c i a l e x p e r i e n c e s p e c i a l i z i n g i n N L P, L L M o r c h e s t r a t i o n , a n d
Predictive Modeling.
P r o v e n t r a c k r e c o r d o f d e v e l o p i n g c o s t - e ff e c t i v e A I s o l u t i o n s ( r e d u c e d i n f r a s t r u c t u r e c o s t s b y u p t o
460x vs cloud providers) and building stateful multi-agent systems using LangGraph.
E x p e r i e n c e d i n e n d - t o - e n d d e p l o y m e n t , f r o m f i n e - t u n i n g o p e n - s o u r c e m o d e l s ( X L M - R O B E RTa ) t o
d e p l o y i n g s c a l a b l e R E S T A P I s o n A z u r e a n d AW S .

SKILLS
A I & M a c h i n e L e a r n i n g : N L P, P re d i c t i ve M o d e l i n g , M u l t i - A g e n t S y s t e m s , L L M O rc h e s t ra t i o n ,
P ro m p t E n g i n e e r i n g , D a t a S c i e n c e , S t a t i s t i c s .
Fra m e w o r k s & L i b ra r i e s f o r m u l t i a g e n t s y s t e m s : Tra n s f o r m e r s ( H u g g i n g Fa c e ) , L a n g C h a i n ,
L a n g G ra p h , L a n g S m i t h , O p e n A I A P I .
B a c ke n d E n g i n e e r i n g : P y t h o n , Fa s t A P I , R E S T A P I s , Po s t g re S Q L , M y S Q L , D j a n g o
C l o u d & D ev O p s : AW S , A z u re ( C o n t a i n e r I n s t a n c e s , B l o b S to ra g e ) , D o c ke r, C I / C D ( G i t H u b
Actions), Git, Linux.

WORK EXPERIENCE

Team Lead AI Engineer | Independent Project | [09, 2025] - present
Autonomous Legal Client Intake System (Telegram)
Architected a multi-agent conversational system using LangGraph to automate the
lead qualification and onboarding process for legal services via Telegram.
Designed specialized LLM agents (Greeter, Qualifier, Data Extractor) orchestrated
through LangChain to handle complex, multi-turn dialogues, ensuring dynamic routing
based on user intent.
Implemented stateful dialogue management to seamlessly guide potential clients
through a structured interview, accurately extracting and summarizing critical personal
and case-specific data.
Containerized the entire application using Docker, establishing a reproducible
environment and independently deploying the containerized microservice to a personal
cloud instance.
Engineered robust prompt templates and guardrails to maintain a professional,
empathetic tone suitable for legal consultations while minimizing hallucinations during
data collection.

Senior AI Engineer / Machine Learning Egnineer | [01, 2025] – [01, 2026]
"Future Graph” Startup
Multi-Agent Orchestration: Architecting and developing a stateful multi-agent system
using LangChain and LangGraph to automate financial market research and analyze
news sentiment.
Predictive Modeling: Designed and trained predictive machine learning
models to forecast BTCUSDT price direction, achieving 60% accuracy, 60%
precision, and 70% recall through advanced feature engineering.
End-to-End Deployment: Built and deployed scalable
REST APIs using FastAPI, Docker, and AWS to serve
predictive models and agentic workflows.
AI & NLP Engineer / Data Engineer | [01, 2024] – [01, 2025]
"PII Removal System" Startup
(GDPR Compliance & Document Anonymization)
DEMO API - https://pii.it-sprout.org.ua/
Custom NLP Pipeline: Developed and fine-tuned a custom Named Entity Recognition
(NER) model based on XLM-ROBERTa. Achieved 97% accuracy across English, Russian,
and Ukrainian languages.
Market-Leading Accuracy: Outperformed out-of-the-box cloud NLP solutions from
AWS, Azure, and Google in accuracy for Slavic languages.
Cost Optimization: Slashed infrastructure costs by 10x to 460x compared to enterprise
cloud NER solutions by heavily optimizing the model for CPU-based inference.
High-Performance Backend: Engineered a REST API using FastAPI capable of
processing and anonymizing 86 document pages (resumes) per minute.
LLM Integration: Implemented automated data quality verification utilizing the OpenAI
API to ensure flawless PII redaction.
Cloud Infrastructure: Managed end-to-end deployment by containerizing the
application with Docker and hosting it on Azure Container Instances alongside Blob
Storage.

Backend / AI Engineer | [01, 2023] – [12, 2024]
AI JobTech Platform
Site for automatizaton of searching job
Backend Development: Architected and developed a FastAPI-based + Django backend
prototype designed to automate the job search process, including resume tailoring and
application outreach.
LLM Integration: Integrated the OpenAI API to dynamically generate personalized
cover letters and adapt resumes based on specific job descriptions and keywords.
Automated Dispatch System: Engineered the core logic and scripts for an automated
email outreach system to send personalized applications to recruiter databases.
Technical Scope: Gained hands-on, from-scratch development experience in
building AI-driven content generation pipelines and orchestrating API
workflows

E D U C AT I O N
Oles Honchar Dnipro National University (DNU)
Bachelor of Applied Mathematics September 2024 — Present (Expected Graduation: 2027)
Currently enrolled in an accelerated 2.5-year Bachelor's program based on my prior college degree.

Machine-Building Professional College of Oles Honchar DNU
Professional Junior Bachelor / Associate Degree in Applied Mathematics September 2020 — June 2024

Languages:
English (B2), Russian (Native), Ukrainian(Native), Czech (B1)