I build reliable backend systems, AI applications, and data infrastructure with a focus on scalability, observability, and production quality.
I am a software engineer and Master of Information Technology student specializing in Artificial Intelligence at UNSW. My experience spans backend engineering, data platforms, distributed systems, LLM applications, and ML infrastructure.
I am interested in building practical systems that are reliable, scalable, and easy to operate in production.
- Backend service design with Python, FastAPI, C++, Java, and SQL
- Data pipeline reliability, observability, anomaly detection, and ETL monitoring
- LLM applications, RAG systems, conversational analytics, and model-serving APIs
- Distributed systems, concurrency, TCP services, and scalable storage
- Cloud-native development with AWS, Docker, Kubernetes, Redis, PostgreSQL, Kafka, and Airflow
KeyMesh — C++, TCP, Multithreading, Distributed Systems
Distributed key-value store with peer replication and thread-safe request handling.
Model Serving Microservice — Python, FastAPI, Docker, Kubernetes, MLflow
Containerized LLM inference service with autoscaling, monitoring, and model versioning.
RAG Document Summarization System — Python, LLM, Retrieval, FastAPI
Retrieval-augmented generation pipeline for document summarization with semantic search and low-latency serving.
I am open to software engineering internship opportunities in backend engineering, AI systems, infrastructure, and data platforms.
