Headline

LLM & MLOps Engineer | Agentic RAG Systems, Multi-Agent AI, Real-Time ML Pipelines | FastAPI • LangGraph • XGBoost • PostgreSQL | IEEE publisher

About

I build production-grade AI systems focused on LLM applications, agentic workflows, and real-time machine learning pipelines. My work is centered on three areas: Agentic AI systems (LangGraph, multi-agent workflows, tool-calling) Retrieval-Augmented Generation (RAG) with evaluation and grounding End-to-end MLOps systems (streaming, drift detection, retraining) Selected work includes: A real-time fraud detection pipeline with automated retraining and 42ms inference latency A multi-agent customer support system with cost-aware routing and human-in-the-loop escalation A contract intelligence platform with clause extraction, risk scoring, and deterministic AI outputs I focus on building systems that go beyond prototypes—deployable architectures with proper evaluation, observability, and cost constraints. Currently seeking roles in: LLM Engineer Applied AI / GenAI Engineer MLOps Engineer

Location

Cuttack

Work experience

Intern at UptoSkills, Jan 2025 - Apr 2025 · 4 mos, Remote, Built an ML-powered MCQ generation system using Python and FastAPI, supporting generation and evaluation of 1,000+ questions Designed API architecture and integrated content evaluation pipeline for full-stack assessment platform Increased backend test coverage from 0% to 80% across core API endpoints through unit and integration testing Improved system reliability and response consistency through structured validation and testing workflows

Education

Bachelor of Technology, Computer Engineering, Centurion University of Technology and Management

Xii, Stewart science college