andrewkobal

Tech stack: TypeScript, Python, Node.js, React Native, MongoDB, Qdrant, LangChain, PyTorch, Transformers, OpenAI API, OpenAI Embeddings, FastAPI, RAG, Generative AI, RabbitMQ, Google Cloud (GCP), Docker, Kubernetes, TanStack Query, Zustand – Implemented a Retrieval-Augmented Generation (RAG) pipeline with Qdrant for AI agent memory and context – Fine-tuned open-source LLMs on custom datasets using Transformers for specialized assistant tasks – Deployed AI models on in-house infrastructure – Built a recommendation engine for a social feed using OpenAI embeddings and Qdrant vector database – Developed and shipped a React Native mobile app with persistent chat, voice, photo, and video integration – Architected an event-driven microservices platform for a multimodal AI app using Domain-Driven Design (DDD) – Managed the full DevOps lifecycle on GCP, including CI/CD pipeline implementation and cost optimization

Tech stack: TypeScript, Node.js, NestJS, Next.js, React, Solidity, PostgreSQL, Redis, Event Sourcing (CQRS), Web3, Generative AI Agents, Google Cloud (GCP), Docker, Kubernetes, TanStack Query, Redux – Architected a DEX and token launchpad where users can trade tokens and launch new coins – Built an AI layer with multiple autonomous agents – Conversational UI agent for chat-based platform management and analytics – Portfolio manager agent to handle user assets – Trading agent to execute trades – Market-making agent to manage token liquidity – Social media agent to promote launches across channels (Twitter, Telegram) with custom plugins for elizaOS – Developed the Model Context Protocol (MCP), a unifying framework that provides access to all platform capabilities and supports building and deploying autonomous Generative AI agents – Extended the AI layer with integrations for external services and automation workflows – Wrote and deployed Solidity smart contracts for token launches, liquidity pools, trading, and market-making agents – Engineered a SOC 2 Type II & ISO/IEC 27001 compliant custodial wallet for the DEX – Developed backend microservices with Node.js, NestJS, PostgreSQL, Redis, and real-time data pipelines for high-frequency trading data – Managed deployment and infrastructure on GCP, implementing CI/CD and cost-control measures

– Built a full-stack client dashboard, developing both backend services and frontend interface – Designed and implemented backend architecture with REST APIs to support complex frontend functionality – Integrated ML model outputs into backend services for real-time data visualization and user interaction – Developed a responsive frontend dashboard for AI/ML analytics, predictions, and reporting tools – Implemented authentication, session management, and role-based access control – Optimized backend and frontend performance to handle high data throughput from ML pipelines – Deployed infrastructure and CI/CD pipelines for efficient development and release cycles

– Delivered multiple full-stack projects across different industries – Designed and maintained scalable backend systems – Built responsive and dynamic frontends, integrating APIs for seamless UX – Collaborated with cross-functional teams to deliver end-to-end solutions – Applied agile methodologies for efficient project delivery and continuous improvement