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AI Engineer with less than a year in AI/ML engineering, RAG pipelines & LLM application development.
AI is analyzing your overall score…
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
IIT Roorkee graduate with experience in AI/ML engineering, agentic AI systems, RAG pipelines, and LLM application development. Skilled in Python, Data Structures Algorithms, LangChain, LangGraph, FastAPI, vector databases, tool calling, guardrails, and workflow orchestration. Experienced in building retrieval systems, multi-agent applications, and production-oriented AI solutions, with a strong interest in Generative AI, Machine Learning, and AI automation.
Indian Institute of Technology, Roorkee
B.Tech. · Mechanical Engineering
August 1, 2022 – June 30, 2026
Helic AI
AI Intern
May 1, 2025 – June 30, 2025
India
MNIT Jaipur
Time Series Research Intern
September 1, 2024 – November 30, 2024
Jaipur, Rajasthan, India
VisionTalk: RAG Chatbot for YouTube Video Q&A
June 24, 2026 – Present
Architected an end-to-end RAG pipeline that transforms any YouTube video into a conversational AI interface via automated transcript extraction and semantic search, eliminating the need to manually scrub through video content. Achieved 40%+ improvement in answer relevance by implementing hybrid retrieval (Dense embeddings + BM25 + Cohere reranking), with a scalable multi-video session-aware API backed by Qdrant vector storage and timestamp-aware responses.
Adaptive RAG Agent with Smart Query Routing
June 24, 2026 – Present
Built a fully Dockerized Adaptive RAG Agent that dynamically routes queries across vector retrieval, LLM reasoning, and live web search, reducing hallucinations by 35% and delivering context-accurate responses at scale via FastAPI and Streamlit. Engineered a thread-based multi-session state management system with SQLite checkpointing and isolated document contexts, enabling zero-loss chat restoration across concurrent user sessions and improving retention UX.
Multi-Agent Dental Appointment Assistant
June 24, 2026 – Present
Designed a production-grade multi-agent AI system using LangGraph and LLMs that fully automates appointment workflows (booking, cancellation, rescheduling, retrieval), reducing scheduling overhead to zero for clinic staff. Implemented intelligent tool-based structured routing with specialized agents, SQLite stateful memory, and a Streamlit chat UI, enabling real-time dynamic agent selection and seamless interaction with a CSV-based appointment backend. Built robust agent guardrails and persistent long-term memory architecture with SQLite, ensuring safe tool execution, reliable workflow control, and cross-session context retention for personalized user experiences.
MIL-505 Statistical Machine Learning
IIT Roorkee
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from RAG chatbots to multi-agent systems and time series analysis, indicates a broad interest in AI/ML applications. Their involvement in a student technical council suggests a collaborative spirit and a willingness to contribute to a technical community. The projects emphasize practical problem-solving and building scalable solutions, which aligns with a results-oriented culture. The candidate's academic background from a reputable institution further supports a strong learning aptitude.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and project ownership through multiple personal projects. Their experience in leading technical events suggests good organizational and leadership potential. The detailed project descriptions indicate an ability to articulate complex technical concepts clearly. The focus on reducing manual effort and improving efficiency in their internship roles aligns well with operational effectiveness.