I build AI systems that solve actual problems. My work centers on agent architectures, backend services, and production-ready machine learning applications.
Core experience:
- Designing multi-agent systems with ADK that handle complex workflows
- Building REST APIs with FastAPI for production environments
- Containerizing and orchestrating services with Docker and Kubernetes
- Implementing vector search and retrieval systems for AI applications
- Training and deploying deep learning models end-to-end
I focus on the full lifecycle: from initial architecture to deployment, monitoring, and maintenance.
Agent Systems
Built production agent systems using ADK with tool integration, state management, and orchestration. These aren't demos—they handle real tasks with error recovery and logging.
VectorMind AI
A retrieval-augmented generation platform using ChromaDB and FastAPI. Deployed in containers with proper separation of concerns. Shows I understand both the ML and engineering sides.
Deep Learning Fundamentals
Implemented optimization algorithms (Momentum, RMSProp, Adam) from scratch. Built classifiers for medical imaging and NLP tasks. I don't just use libraries. I understand what's happening under the hood.
- Expanding monitoring and observability practices for ML systems
- Building more sophisticated agent coordination patterns
- Contributing to open source tools I actually use
- Studying distributed system design for AI workloads
I learn by building. Check the repositories to see what I've actually made.