Work experiences

A chronological journey through my professional milestones, from distributed systems and cybersecurity to advanced GenAI ecosystems.

Magnum Opus AI Ecosystem | Design Architect & Developer

Feb 2026 - Present
  • ▹Building an AI Ecosystem featuring custom-trained LLMs, vector databases, and autonomous agents for specific core use cases.
  • ▹Developing a hybrid RAG architecture to support complex domain-specific queries and automation.

Project Management Suite | Developer

Feb 2026 - Present
  • ▹Architecting an offline project management utility to track project variables and embedded management use cases.
  • ▹Focusing on high-performance local data handling and extensive management utility features.

Distributed LLM Inference Platform | Developer

Jan 2026 - Present
  • ▹Developed a production-style distributed inference system using Python, FastAPI, and Redis for serving local GGUF models.
  • ▹Implemented a scalable architecture: Client → API Gateway → Cache → Worker Nodes → LLM.
  • ▹Optimized for low-latency request handling and efficient load balancing across local inference workers.

Tech Chronicles | Developer

Jan 2026 - Feb 2026
  • ▹Developed a chronological blogging platform to document and share long-term technical experiences.
  • ▹Architected the initial version using PostgreSQL, Redis, and FastAPI for efficient data handling.
  • ▹Successfully refactored the application to leverage a modern tech stack for improved performance and scalability.

RAG Chatbot V2 (Production-Ready) | Developer

Jan 2026 - Feb 2026
  • ▹Architected a high-performance, production-ready RAG system utilizing LangGraph for complex stateful agent orchestration.
  • ▹Integrated Qdrant as a high-speed vector store with PostgreSQL for persistent memory, ensuring data integrity and long-term context retention.
  • ▹Built a seamless Next.js 14 frontend, optimized for real-time streaming of LLM responses and complex agent-tool interaction.

RAG Chatbot V1 (Prototype)| Developer

Jan 2026 - Feb 2026
  • ▹Developed a local, hybrid AI agent platform designed for rapid experimentation with pluggable tools and modular RAG storage.
  • ▹Leveraged Chainlit for an accelerated, feature-rich conversational UI, significantly reducing development time for new AI agent use cases.
  • ▹Implemented flexible LangChain tool-calling capabilities that allow the agent to switch dynamically between local inference and external data sources.