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AI/ML Engineer with less than a year in Generative AI & LLMs
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Assessing your cultural and operational fit
AI/ML Engineer with hands-on expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Natural Language Processing (NLP). Proficient in designing end-to-end LLM pipelines, vector embedding architectures, and AI agents using LangChain, FastAPI, and Hugging Face. Adept at prompt engineering, semantic search, and deploying intelligent automation systems at scale. Passionate about real-world impact through AI-driven solutions.
Sri Venkateswara University
B.Tech · Computer Science & Engineering
August 1, 2022 – June 30, 2026
Coincent.ai (E-Cell IIT Madras)
Data Science & AI Intern
February 1, 2024 – March 31, 2024
India
Equity Research Dashboard — AI-Powered Financial Intelligence Platform
June 24, 2026 – Present
Built a RAG-powered financial intelligence platform using LangChain, Google Gemini, and FAISS for context-aware Q&A over financial reports. Designed semantic retrieval pipelines with vector embeddings enabling low-latency search across large financial datasets. Deployed an interactive Streamlit dashboard delivering source-grounded LLM responses for investment research workflows.
Multi-Document RAG Assistant — Generative AI Knowledge Retrieval System
June 24, 2026 – Present
Developed a multi-document RAG assistant supporting PDF, DOCX, TXT, CSV, XLSX, and URL ingestion using LangChain and FAISS. Implemented chunking, embedding generation, vector indexing, semantic retrieval, and citation-aware responses for accurate knowledge extraction. Integrated Llama 3.3 70B via Groq API with intelligent routing between document-grounded and general-purpose LLM conversations.
Job Description Simplifier — AI-Powered Recruitment Intelligence Tool
June 24, 2026 – Present
Built an end-to-end NLP application powered by Llama 3.3 70B via LangChain and advanced prompt engineering to parse and structure complex job descriptions into actionable summaries. Developed a web-scraping and content-preprocessing pipeline for automated large-scale collection and normalisation of job posting data, demonstrating ETL and data engineering proficiency. Implemented LLM-based information extraction to surface key skills, roles, and responsibilities from unstructured text; deployed Streamlit UI for rapid role-fit assessment.
Google AI Essentials
Coursera
June 1, 2026 – Present
Artificial Intelligence with Python
E-Cell IIT Madras
June 1, 2026 – Present
RescueGrid: A Real-Time Bio-Logistics and Emergency Donor Matching System
AIJFR Journal
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity (recruitment, finance, general knowledge retrieval) and participation in hackathons suggest a proactive, curious, and adaptable individual. The alignment of personal projects with the target role of AI/ML Engineer indicates strong intrinsic motivation and a passion for the field, which is a positive cultural fit. The academic background in Computer Science & Engineering further supports a structured learning approach.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to translate complex technical concepts into functional applications. The internship experience suggests a capacity for structured problem-solving and delivering actionable insights. The focus on end-to-end solutions implies a good operational fit for roles requiring full lifecycle development.