- 🌱 Currently improving DevOps and scalable system design
- 🤝 Open to collaborating on large-scale web / AI applications
- 💬 Ask me about backend systems, RAG, and AI integrations
- 📫 Reach me: artemiifrid@gmail.com
- Retrieval-Augmented Generation (RAG)
- LLM systems, RLHF, Model Evaluation
- Scalable backend architecture (Spring Boot, Node.js)
- CI/CD, containerization, cloud deployment
- Developed backend and frontend features using Spring Boot, TypeScript, Docker
- Built and deployed services in a containerized Azure environment
- Implemented JUnit + Mockito testing, reducing defects by ~30%
- Collaborated in Agile team using Jira, Git workflows
- Led development of cross-platform app using Flutter + BLoC
- Integrated backend with Spring Boot REST APIs
- Used Firebase for real-time data and authentication
- Designed scalable architecture (MVVM) and collaborated via Agile
- Improved LLM performance using RLHF techniques
- Evaluated outputs for reasoning, accuracy, and linguistic quality
- Built “Backboard” RAG memory system using Python, Redis, MongoDB for long-term contextual recall
- Developed AI ↔ user chat system integrating retrieval + generation pipeline
- Implemented AI onboarding flow to capture user context and generate voice profile baseline
- Engineered pipelines for personalized inference and behavioral feedback
- Delivered full-stack apps using Flutter, Java, Rust (Axum), Node.js
- Managed full lifecycle: development → deployment (Docker, AWS)
- Backend engineering (Spring Boot / Node.js)
- AI-powered applications (RAG, LLM systems)
- DevOps & scalable infrastructure