Generative AI Engineer with less than a year in LLMs, RAG pipelines, and Python.
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Assessing your cultural and operational fit
Computer Science fresher with hands-on expertise in LLMS, RAG pipelines, and Lang Chain. Built and deployed 3 Gen Al projects end-to-end. Strong foundation in Python, Deep Learning, and Transformer architecture. 100+ LeetCode problems solved.
KCCITM
B.Tech · Computer Science & Engineering
August 1, 2022 – June 30, 2026
YouTube Video Q&A Chatbot
January 1, 2026 – June 11, 2026
Built a RAG-based chatbot that answers questions about any YouTube video by extracting its transcript via youtube-transcript-api and indexing it in a FAISS vector store. Integrated LangChain conversation memory for multi-turn Q&A; deployed as a Streamlit app supporting videos up to 3 hours long.
View ProjectDocuMind - RAG-Powered Document Q&A System
January 1, 2026 – June 11, 2026
Built an end-to-end RAG pipeline using LangChain, FAISS, and OpenAI GPT-4o to answer questions over large PDF corpora; achieved ~88% accuracy on a custom eval set. Reduced hallucination rate by 35% vs. vanilla LLM via grounded retrieval; deployed as a Streamlit web app with source citations and conversation memory.
View ProjectSMS Spam Detection System
January 1, 2026 – June 11, 2026
Built an end-to-end SMS spam classifier using NLP and machine learning (scikit-learn); trained on the UCI SMS Spam Collection dataset with text preprocessing via NLTK (tokenization, stopword removal, stemming, TF-IDF vectorization). Deployed the full application with a separate backend and frontend structure; packaged model with pickle for production serving.
View Project100+ Problems Solved
LeetCode
June 11, 2026 – Present
Transformer-from-Scratch repo
GitHub
June 11, 2026 – Present
LangChain for LLM Application Development
DeepLearning.AI
January 1, 2024 – Present
NLP with Transformers Course
HuggingFace
January 1, 2024 – Present
Building Systems with the ChatGPT API
DeepLearning.AI
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, focusing on practical applications of AI/ML, aligns well with an innovative and results-oriented culture. The self-driven learning and project development suggest a proactive and curious individual. The target role of 'Generative AI Engineer' is a strong match for the candidate's demonstrated skills and project focus. However, the lack of team-based project experience or professional roles limits the assessment of collaboration and broader cultural integration.
Soft Skills & Operational Fit
The candidate demonstrates initiative and a strong learning aptitude through personal projects and certifications. The project descriptions indicate an ability to work independently on complex technical challenges. However, without direct work experience or behavioral assessment data, it is difficult to fully assess operational fit, teamwork, and communication in a professional setting.