AI Engineer with less than a year in LLM & Data Analytics
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Third-year CSE student specializing in LLM application development and Applied AI - RAG pipelines, agentic AI systems, NLP-driven tools, and REST API deployment using Python, LangChain, Hugging Face, and Groq. Built and shipped 2 end-to-end AI POCs with FastAPI backends and vector search. Proven ability to deliver data engineering workflows and analytical dashboards through internship and self-driven projects.
Arya College of Engineering, Jaipur
B.Tech · Computer Science Engineering
August 1, 2023 – Present
Airkrit India (Formerly Edulyt India)
Data Analyst Intern
June 1, 2025 – August 31, 2025
Delhi, Delhi, India
AI Study Buddy
January 1, 2025 – Present
Developed an AI POC enabling document-grounded Q&A via a LangChain RAG pipeline backed by ChromaDB vector search, achieving sub-2s query latency on 50+ ingested documents. Deployed a Streamlit frontend with modular FastAPI backend; implemented flashcard generation via Groq LLaMA and map-reduce summarization for long documents, reducing context overflow by ~60%. Integrated OCR-based document ingestion supporting scanned PDFs and images, expanding compatible input formats by 3x. Implemented semantic chunking and embedding optimization strategies, improving retrieval relevance (top-k accuracy) and reducing hallucinations in generated responses.
View ProjectLinkedIn Post Generator
January 1, 2025 – Present
Designed an NLP-driven style-transfer pipeline extracting linguistic features from posts using HuggingFace all-MiniLM-L6-v2 embeddings stored in ChromaDB; retrieval accuracy ~88% on evaluation set. Built a FastAPI REST API backend with configurable tone-controlled generation (professional, casual, storytelling) via semantic vector retrieval; 3 output styles with <1.5s response time. Exposed a REST endpoint consumed by a Streamlit demo UI, enabling one-click post generation with real-time tone switching. Integrated prompt engineering with few-shot examples and dynamic context injection, improving content coherence and style consistency across generated posts.
View ProjectCredit Card Transaction Analysis
January 1, 2025 – Present
Conducted feature extraction and pattern mining on 10,000+ credit card records to surface spending trends, repayment behavior, and profit drivers across customer segments. Built Scikit-learn predictive models achieving 82% accuracy to forecast repayment risk and segment high-profit cohorts; delivered Power BI dashboards adopted for stakeholder reporting. Visualized spending patterns and repayment trends across 5+ customer cohorts in interactive Power BI dashboards, reducing manual reporting time by ~35%. Performed data preprocessing and feature engineering (handling missing values, scaling, encoding), improving model performance and stability across validation datasets.
View ProjectGoogle AI Agents Bootcamp
January 1, 2025 – Present
Cultural Fit Analysis
The candidate shows a strong passion for AI through diverse personal projects (AI Study Buddy, LinkedIn Post Generator, Credit Card Transaction Analysis) and organizing an AI festival. This indicates a proactive, self-driven individual who is likely to thrive in an innovative and fast-paced AI-focused environment. The breadth of skills across NLP, RAG, and predictive analytics, combined with experience in both data analysis and AI development, suggests adaptability and a willingness to learn new technologies. The Google AI Agents Bootcamp further reinforces a commitment to staying current with industry trends.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems, optimize performance (e.g., sub-2s query latency, reducing context overflow), and deliver functional solutions. The 'Neural Nexus AI Fest' organization suggests leadership and event management skills, which can translate to good team collaboration and initiative. However, without direct interview data, specific soft skills like stress handling or detailed communication clarity cannot be fully assessed.