Open to opportunities

Krrish Yaduka

@krrishyaduka

AI Engineer specializing in Applied AI, LLM systems, and multi-agent architectures—building production RAG and agentic workflows.

India

Message

What I'm looking for

I’m looking to build production-grade Applied AI: LLM systems, RAG pipelines, and multi-agent workflows. I want to ship reliable, real-world solutions in domains like healthcare or fintech, with a team that values strong engineering.

I’m an Applied AI Engineer focused on Generative AI, LLM systems, and multi-agent architectures. I build production-grade Applied AI solutions, including RAG pipelines and agentic AI workflows.

I design and deploy systems using LangChain, LangGraph, FastAPI, and Python, with experience across healthcare, fintech, and HR domains. I’m hands-on with prompt engineering, model evaluation, and vector databases like Pinecone and FAISS.

I’ve also built multi-agent products and hackathon projects—from a conversational PDF assistant (DocFlow AI) to an AI hiring copilot (TalentOS) and contract review automation (ClauseGuard India). My goal is to ship reliable, real-world AI that’s secure, testable, and measurable—backed by practical deployment on GCP.

Experience

Work history, roles, and key accomplishments

AI Intern

MiraiS chool of Technology

Jul 2025 - Aug 2025 (1 month)

Built an AI-powered conversational chatbot leveraging NLP and generative AI. Applied prompt engineering to improve multi-turn response relevance and conversational quality, implemented intent/context/fallback logic in Python, and iteratively improved outputs through evaluation.

Generative AI NLP Prompt Engineering LangGraph Multi Agent Systems RAG Python Conversational AI Fallbacks

Education

Degrees, certifications, and relevant coursework

Adamas University

Bachelor of Technology (B.Tech), Artificial Intelligence / Machine Learning

Grade: 8.1/10.0

Final-year B.Tech student focused on AI/ML and multi-agent architectures, with a CGPA of 8.1/10.0. Builds Applied AI solutions including RAG pipelines and agentic workflows.