I build scalable backend systems and develop autonomous AI agents. My focus is on turning machine learning models into production-ready, reliable architecture with clean, type-safe code..
- Production-ready backend architectures & container orchestration.
- Agentic AI workflows & multi-agent systems.
- Writing highly optimized, low-level & mathematical code from scratch.
- Distributed Systems — scalability, fault tolerance, and service communication.
- Docker & Kubernetes — containerization, orchestration, and deployment strategies.
- Advanced Backend Engineering — asynchronous programming, caching, message queues, and API optimization.
- LLM Engineering & Agentic AI — multi-agent orchestration, tool calling, memory, and autonomous workflows.
- Deep Learning Mathematics — implementing neural networks and optimization algorithms from first principles.
- System Design — designing scalable APIs, databases, and cloud-native services.
- Full-Stack Development — building modern web applications with responsive frontends, scalable backend APIs, and database integration.
- Agentic Workflows: Developed and deployed multi-agent systems using Fetch.ai and Google ADK 2.0 for cybersecurity automation, DevOps pipelines, and e-commerce rescue operations across hackathons like PI Innovate, CortexX, and AI Seekho.
- Zero-Trust-Web-Guardian: A collaborative security project focused on secure backend infrastructure and real-time threat mitigation.
Built a modular, object-oriented deep learning framework completely from scratch utilizing NumPy for vectorization, forward/backward propagation, matrix calculus, and gradient descent optimization — entirely bypassing high-level ML libraries to master the mathematical foundations of deep learning.
- omegaUp: Contributed to internal tooling by refactoring legacy Redis logic into strict type-safe code using Mypy, resolving technical debt in background cron jobs and worker nodes, and improving maintainability.