AI Engineer with less than a year in LLM application development & fullstack.
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Asmi Shetty is an aspiring AI Engineer with 9 months of intensive internship experience in software development and AI/ML applications. She has actively contributed to enhancing a full-stack AI platform and developing an ABDM-aligned healthcare portal. Her expertise spans advanced AI/ML concepts including Agentic Systems, RAG, Generative AI, and LLM Application Development, demonstrated through impactful projects like an AI-powered meeting assistant and an NL-to-SQL agent. She is proficient in Python, React.js, Node.js, and various databases, coupled with strong problem-solving and teamwork skills.
Shri Guru Gobind Singh Ji Institute of Engineering and Technology
Bachelor of Technology · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Arithwise Solutions
Software AI Developer Intern
December 1, 2025 – April 1, 2026
Nagpur, Maharashtra, India
Avijo Healthcare
Software Developer Intern
April 1, 2025 – July 1, 2025
India
QueryIQ: NL-to-SQL Agentic Assistant (LangChain + Mistral AI)
June 24, 2026 – Present
Built an NL-to-SQL agent using LangChain + Mistral AI that converts queries into validated SQLite SELECT statements, reducing manual query writing by 80% with a 2-retry self-correction loop achieving 90% runtime success rate. Implemented a multi-layer SQL guardrail system blocking 5+ threat patterns (injection, DROP/DELETE, system-table access) with pandas-powered result retrieval returning query time and row count metadata. Developed a Streamlit chat interface with multi-turn memory over a 4-table, 160+ row SQLite database covering employees, projects, and salaries. Tech stack: Python, LangChain, Mistral AI, Streamlit, SQLite, pandas, Faker, python-dotenv.
AI Meeting Intelligence and RAG Assistant
June 24, 2026 – Present
Designed an AI-powered meeting assistant that transcribed 100+ hours of multilingual meeting recordings (English, Hindi, Hinglish) from YouTube URLs, audio, and video files, generating structured summaries and insights. Built a RAG-based conversational chatbot using LangChain, ChromaDB, and Hugging Face Embeddings, enabling users to query 1,000+ meeting transcript chunks through natural language interactions. Automated extraction of action items, key decisions, open questions, and follow-ups, with support for exporting comprehensive meeting reports in PDF and TXT formats. Tech stack: Python, LangChain LCEL, OpenAI Whisper, Sarvam AI, Mistral AI, ChromaDB, Hugging Face Embeddings, RAG, Streamlit.
Cultural Fit Analysis
The candidate's projects demonstrate a proactive and innovative approach to problem-solving, particularly in AI/ML. The diversity of projects (NL-to-SQL, meeting intelligence, healthcare portal) indicates adaptability and a broad interest in applying technology to different domains. The listed 'Other Skills' (Communication, Teamwork, Leadership, Problem-Solving) suggest an awareness of collaborative work environments. However, the limited professional experience (internships) means cultural fit is primarily inferred from project work rather than extensive team collaboration history.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving, teamwork, and communication skills, particularly in designing and implementing complex AI systems. The ability to work with diverse technologies and integrate multiple modules suggests good operational fit for dynamic development environments. However, the experience level is still early career, which might require more structured guidance in a senior role.