Michael Zmyslony

Architected and delivered AI-powered, cloud-native software solutions for global clients in fast-paced enterprise delivery environments. Built full-stack applications using TypeScript/Node.js and Python, implementing REST APIs, role-based access control, and asynchronous processing for real-time AI-driven features. Deployed and scaled on Google Cloud Platform and Firebase with managed databases, load balancers, and CDN services to ensure low-latency delivery. Integrated AI services by building middleware that connects client CRM and CMS systems with LLM endpoints, enabling semantic search, intelligent recommendations, and contextual chat features. Implemented vector databases for semantic retrieval and improved AI context relevance in production. Set up automated testing and CI/CD pipelines using GitHub Actions and Docker, reducing release rollbacks by 40%. Delivered multiple AI-enabled MVPs and production-ready solutions under tight deadlines.

Led development of scalable AI-powered microservices using FastAPI, improving API performance by 40% and enabling seamless integration across enterprise platforms. Designed and implemented LLM-based workflows using LangChain, vector databases, and Retrieval-Augmented Generation (RAG) to support intelligent search, automation, and AI-driven features. Built and optimized AI data pipelines and asynchronous processing systems using RabbitMQ, Redis, and PostgreSQL for high-throughput workloads. Migrated legacy Streamlit-based AI tools into modern Angular + FastAPI architectures, improving maintainability, scalability, and user experience. Developed distributed cloud infrastructure on AWS and Azure using Docker, Kubernetes, and Terraform, supporting reliable deployment of AI services and backend systems. Enhanced observability and monitoring with OpenTelemetry, structured logging, and distributed tracing for production-grade AI applications. Collaborated with engineering teams to improve AI

Led migration of large-scale enterprise applications from legacy Angular to modern frameworks, restructuring UI/UX architecture, reducing technical debt, and cutting build times by 35%. Developed location-based services using geolocation APIs to drive service discovery and targeted user experiences. Integrated CRM platforms for personalized promotions and behavior-based messaging. Engineered secure transaction workflows with third-party gateways, improving checkout success rate. Optimized front-end performance through code splitting, lazy loading, and HTTP request minimization, reducing first render time by 20%. Mentored junior developers and collaborated with QA teams to ensure regression-free deployments across multiple brand tenants.