I enjoy building production-style backend systems and AI-powered applications. My primary interests are backend engineering, distributed systems, LLM applications, and designing software that solves real business problems.
- Backend Software Engineer
- Building AI-powered applications using modern LLMs
- Interested in scalable backend architecture and distributed systems
- Currently learning advanced System Design, AI Infrastructure, and Kubernetes
- Passionate about continuously improving as an engineer
Languages: Python, SQL, JavaScript
Backend: FastAPI, REST APIs, SQLAlchemy
Databases: PostgreSQL, MySQL, MongoDB
AI: Prompt Engineering, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Model Fine-Tuning, Model Evaluation, Generative AI
Concepts: Distributed Systems, Microservices, System Design, CI/CD pipelines
DevOps & Tools: Docker, Git, GitHub Actions, Postman, Linux, Jira
A distributed payment processing platform built to simulate real-world payment infrastructure.
Features include:
- REST APIs
- Transaction lifecycle management
- Background task processing
- Idempotent APIs
- Retry handling
- Metrics collection
- Dockerized deployment
Tech Stack
Python • FastAPI • PostgreSQL • Redis • Celery • Docker
An enterprise AI assistant that enables natural-language interaction with organizational knowledge.
Features include:
- Retrieval-Augmented Generation (RAG)
- Semantic Search
- Query Enhancement
- Local LLM inference
- PostgreSQL + Qdrant
- Enterprise document retrieval
Tech Stack
Python • FastAPI • PostgreSQL • Qdrant • Ollama
I'm particularly interested in building software involving
- Backend Engineering
- Distributed Systems
- AI Applications
- LLM Engineering
- Enterprise AI
- System Design
- Cloud-native Applications
- AI Agents
- MCP (Model Context Protocol)
- Kubernetes
- Kafka
- Advanced Distributed Systems
- Production AI Infrastructure