AI Engineer with less than a year in AI SaaS product development and LLM pipelines
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Final-year CSE student who shipped a live AI SaaS product to real users, built multi-agent LLM pipelines, and deployed ML models end-to-end in production. Looking for an AI/ML internship where output matters more than GPA.
Vivekananda Global University
B.Tech · Computer Science & Engineering
August 1, 2023 – June 30, 2027
Aishly Public School
Higher Secondary & Secondary Education
June 1, 2020 – May 31, 2023
Rama's Ladies E-commerce Store
Marketing-Business Strategy Consultant
January 1, 2024 – Present
Jaipur, Rajasthan, India
AI Review Analyzer SaaS
January 1, 2026 – Present
Built a production-ready full-stack SaaS application that ingests product reviews and returns sentiment analysis, topic extraction, and AI-generated summaries via a Streamlit dashboard. Implemented NLP pipeline using cardiffnlp/twitter-roberta-base-sentiment-latest for sentiment classification and KeyBERT for keyword/topic extraction from unstructured text. Designed async task queue with Celery + Redis for batch review processing; managed PostgreSQL schema with SQLAlchemy ORM and Alembic migrations. Deployed backend on Railway and frontend on Streamlit Cloud with JWT-based authentication; live at getupdate.streamlit.app.
Telegram Daily Task Reminder Bot
January 1, 2025 – Present
Built and deployed a live Telegram bot that lets users schedule tasks with date, day, and time details, then delivers timely notifications via the Telegram API. Persists user task data using SQLite; supports multi-turn conversation context and gracefully handles edge cases such as empty inputs and duplicate entries. Serving active users with consistent uptime; handles concurrent sessions via async Python handlers with graceful error recovery.
Machine Learning with Python
Coursera
June 1, 2026 – Present
Building Agentic AI and Workflows (LangChain, LangGraph, Crew AI, AutoGen, BeeAI)
IBM
June 1, 2026 – Present
Deep-Learning and neural networks with Keras
IBM
June 1, 2026 – Present
Achieved 94%, indicating a near-perfect understanding and application of data science and artificial intelligence principles relevant to the test.
Strengths
Cultural Fit Analysis
The candidate's projects demonstrate a strong initiative and a passion for building practical AI solutions. The focus on shipping live products and handling real-world scenarios aligns well with a results-oriented culture. The academic projects show a willingness to learn and apply new technologies. The certifications indicate a commitment to continuous learning in AI/ML. The candidate's profile suggests a self-starter who is eager to contribute meaningfully.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a focus on delivering functional, user-facing applications. The 'AI Review Analyzer SaaS' project highlights an ability to manage complex system architectures and deploy to production, suggesting good operational fit. The 'Telegram Daily Task Reminder Bot' shows attention to user experience and error handling. The freelance marketing experience, while not directly technical, suggests an understanding of business metrics and data-driven decision-making.
Limitations