Open to opportunities

Ramanand R

@ramanandr

Message

Data Scientist and NLP/LLM engineer building production RAG and agentic AI for enterprise automation.

India

Message

What I'm looking for

I’m looking to build scalable agentic AI and RAG systems for enterprise customer workflows—combining strong ML engineering, rigorous testing, and measurable improvements through A/B testing and evaluation.

I’m a Data Scientist and Software Engineer with 1+ year of hands-on experience in machine learning, NLP, and LLM-powered application development. I build scalable, production-grade systems—especially Retrieval-Augmented Generation (RAG) and semantic search APIs—that reliably improve real workflows.

I’m proficient in Python and modern LLM orchestration with LangChain and LangGraph for stateful, agentic AI workflows. I’ve integrated OpenAI and Anthropic LLM APIs, implemented fine-tuning with LoRA/PEFT via Hugging Face, and delivered measurable gains like ~30% better support ticket auto-routing accuracy and ~40% less manual handling for tier-1 queries.

I focus on rigorous engineering: test-driven development with pytest (maintaining >85% coverage), prompt evaluation with BLEU/ROUGE/F1, and A/B experimentation with statistical significance. From RESTful APIs to deployment on AWS EC2 with Docker, I enjoy turning ML prototypes into dependable enterprise-ready products.

Experience

Work history, roles, and key accomplishments

Current

Junior Software Engineer

Current

Bobcares

Oct 2024 - Present (1 year 8 months)

Develop and maintain Python NLP pipelines for text classification, intent detection, and entity extraction, improving support ticket auto-routing accuracy by ~30% and reducing resolution time by 20%. Built LangChain/LangGraph agentic workflows and integrated OpenAI/Anthropic LLM APIs to automate tier-1 support, reducing manual handling by ~40%.

Python OpenAI API Anthropic Lang Chain LangGraph RAG Pytest

Backend Python Developer

Freelance

May 2024 - Oct 2024 (5 months)

Designed and shipped REST APIs and LLM-powered features with Python, FastAPI, and OpenAI API integrations, deploying containerized services on AWS EC2 via Docker and cutting deployment time by 60%. Built RAG solutions with ChromaDB and delivered an AI web scraping/data extraction API using Puppeteer and Express.js, saving clients ~15 hours/week of manual work.

fastAPI OpenAI API Docker AWS EC2 REST API Development Data Pipelines ChromaDB Puppeteer

Education

Degrees, certifications, and relevant coursework

University College of Engineering, Thodupuzha

Bachelor of Technology (B.Tech), Computer Science and Engineering

2020 - 2024

B.Tech in Computer Science and Engineering with coursework including machine learning, neural networks, statistical methods, data structures and algorithms, database systems, and software engineering.