serhiiliutov

- AI Agent Architecture: Architected “StageCraft”, an enterprise-grade multi-agent platform automating CI/CD migration (Jenkins to GitHub Actions/GitLab). Orchestrated LangGraph agents via AWS Bedrock for Context-Based Learning (CBL) and iterative code refactoring. - Multi-Tenant Deployment: Migrated legacy architectures to Chainlit leveraging MCP (Model Context Protocol) and Playwright, delivering an adaptable AI agent system for multiple enterprise clients. - Backend Engineering: Built a high-concurrency FastAPI microservice architecture using Python and SQLAlchemy. Solved critical race conditions via database constraints and optimized connection pooling for high-throughput agent workloads. - Production Hardening: Enforced enterprise security standards including strict SSL/TLS database connections, environment-aware configuration, and sensitive credential redaction in telemetry logs. - DevOps & Infrastructure: Standardized the development lifecycle using Docker and Alembic, automating schema migrations and integrating a full-stack local environment (Vite/React/Angular + FastAPI + Postgres). - LLM Integration & RAG: Implemented RAG pipelines and HITL (Human-in-the-Loop) workflows to validate and refine AI-generated pipeline configurations.

- Recommendation System Engineering: Engineered a hybrid recommendation pipeline using XGBoost for opportunity ranking and SHAP for explainable AI, providing personalized DeFi yield strategies. - Generative AI & LLM Integration: Developed an LLM-powered "Mood Explainer" service using Google Gemini and LangSmith to transform user behavioral data into human-readable narratives with strict JSON validation. - High-Load API Architecture: Architected a scalable FastAPI microservice with SQLAlchemy and PostgreSQL, leveraging robust caching and database optimization to handle high-concurrency requests. - Data Engineering: Implemented automated ETL jobs to normalize cross-chain DeFi yield data from sources like Coingecko and DefiLlama. - DevOps: Fully containerized the application with Docker and managed database schema migrations via Alembic for reproducible deployments.

- Advanced Analytics: Built 30+ complex dashboards on Dune Analytics covering trader segmentation, user churn, stop-loss behavior, bridging costs, gas usage, and open interest analysis across multiple EVM chains. - Financial Modeling: Designed SQL models tracking PnL vs Pool Value, borrow fee simulations, price impact metrics, and protocol fee projections. - Derivative Performance Analysis: Conducted comprehensive analysis of derivative products (BTC, ETH, LP tokens) through fee tracking, utilization monitoring, liquidity analysis, and TVL trends. - Competitive Benchmarking: Performed competitive benchmarking of other top perpetual DEXes, delivering actionable insights for feature prioritization, liquidity design, and user retention improvements. - ETL Development: Maintained real-time hourly ETL pipelines using Dune’s Spellbook architecture (Dune SQL, dbt, and Trino DB connector) to aggregate and normalize cross-chain data for protocol health monitoring.

- Data Pipeline Engineering: Built and maintained Dagster and dbt pipelines to collect and transform raw data into structured Snowflake analytics datasets. - Analytics & KPIs: Calculated key behavioral indicators (Engagement Score, Retention Metrics) using Snowflake SQL to drive user segmentation and search optimizations. - Visualization & Reporting: Created interactive Power BI dashboards to visualize platform distributions and leveraged AI features for automated narrative insights. - Public Analytics: Replicated internal analytics pipelines for transparent public reporting and external stakeholders.

- AI Platform Development: Engineered a Retrieval-Augmented Generation (RAG) AI platform using LangChain and OpenAI to query a multimodal knowledge base of 1,000+ proprietary projects. - Autonomous Agents: Fine-tuned LLM-based agents for structured summarization, entity extraction, and automated metadata labeling. - Multimodal Pipelines: Developed AI pipelines combining image-to-text models and PDF parsers for comprehensive due diligence.

- Enterprise Chatbots: Built LLM-powered chatbots using OpenAI and LangChain, integrated with Snowflake for enterprise knowledge retrieval. - NLP & Predictive Modeling: Applied prompt engineering for text classification and developed Monte-Carlo models for team productivity and risk simulations.

- Fraud Detection: Applied graph-based machine learning to trace anomalous transaction flows across networks, identifying $12M in compromised funds. - Entity Recognition: Developed NER models with BERT for automated entity extraction from unstructured documents.