Anish Kumar Thakur

I’m an AI Engineer and Computer Science graduate specializing in LLM applications, Retrieval-Augmented Generation (RAG), and multi-agent systems, backed by strong backend engineering in Python, FastAPI, and REST APIs. I focus on turning research capabilities into scalable, production-grade AI systems.

During my Backend Engineer Intern experience at NextClass (Upclick Labs), I built backend services and REST APIs with FastAPI, applying Low-Level Design (LLD) for an EdTech platform. I also automated up-to-date student and college data collection through a RAG pipeline using web scraping and a caching layer, and optimized backend/database queries to cut login latency by 2.1s.

I’ve published as first author at ICMLT 2026 (Berlin, IEEE Germany Section) on an LSTM framework for class-imbalance mitigation in multi-class stock-chart pattern recognition (accepted to IEEE Xplore, in press). I enjoy pairing strong ML/NLP fundamentals with practical engineering—deployment, evaluation, and monitoring—to ship systems that behave reliably under real constraints.

In projects like SwarmOps and QueryGuard, I’ve designed multi-agent pipelines with LangGraph, built async FastAPI backends with WebSocket streaming, and applied governance and validation stacks for safer LLM-driven workflows. I’m excited to contribute to teams where rigorous engineering meets impactful AI applications.