- Banking Agents: Designed and deployed a multi-agent system for SME clients (IP/TOO) that automates routine financial operations, including wire transfers, invoice generation, and account queries via Function Calling and Agentic RAG. - High-Impact NLP Solutions: Engineered an LLM-powered Call Center orchestration layer that reduced manual workload by 35% and optimized support operational costs. - Advanced RAG Architecture: Developed a sophisticated RAG pipeline utilizing Hybrid Search, Re-ranking, and Embedding optimization to power document intelligence and fraud detection systems. - Enterprise MLOps: Scaled production infrastructure using vLLM, Docker, and CI/CD pipelines, implementing automated monitoring and model retraining for high-load banking services. - Strategic Leadership: Led technical alignment of ML initiatives with business goals and mentored a team of data scientists, establishing modern standards for LLM development and evaluation.

End-to-End AI Recruitment System: Designed and led the development of an autonomous recruitment agent automating the full cycle: job description generation, CV parsing/ranking via RAG, and real-time voice interviews. - Team Leadership: Managed a cross-functional team of 5 (2 Backend, 2 Frontend, 1 PM), defining technical roadmaps, architecture, and task delegation. - Voice Integration: Implemented low-latency Speech-to-Text and TTS pipelines for automated candidate screening calls. - System Logic: Developed a custom multi-agent orchestration layer using FastAPI and Python to ensure reliable interaction between specialized LLM agents.

•Model development and implementation: Creation and implementation of advanced machine learning models for text classification and clustering, including using large models •Optimization and updating of the chatbot: Regular updates, bug fixes and adding new features to the chatbot model, increasing its efficiency and functionality. •Data analysis and processing: Collecting and processing incoming calls, uploading/uploading data from a database, analyzing large amounts of data in SAS to identify cost savings opportunities for the bank. •Hypotheses and Analytics: Hypothesis testing and data analysis, including analysis of the results of A/B testing on calls, to improve business processes. •Visualization of business metrics: Development and planning of visualization of various business metrics for better understanding and decision-making. •NLP Technologies: The application of advanced natural language processing techniques to improve internal processes and customer experience.

• Analysis of KPI, salary and motivation indicators • Development of a sales evaluation system for the pharmaceutical market with "Viostis" • Presentation of quarterly reports with visualization of dashboards • Compilation of a monthly sales monitoring file with a Customer Relationship Management System "CRM" • Control and Analysis of financial risks • Optimization of processes and structures

• Data collection for analysis • Reporting on the employee attendance control system • Data reconciliation and cleaning