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AI Engineer with less than a year in LLM Applications & Agent Development
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Assessing your cultural and operational fit
AI Engineer with hands-on experience building production-grade LLM applications, RAG pipelines, and AI agents. Proficient in LangChain, ChromaDB, Gemini API, and OpenAI. Built and deployed voice-enabled AI agents, fake news detection systems, and a custom 1-bit Small Language Model. Six-month internship at Tata Insights and Quants (Tata Industries) delivering ML-ready datasets and React frontends. Passionate about agentic AI, multi-modal systems, and scalable LLM deployment.
KMCT Institute of Emerging Technology. APJ Abdul Kalam Technological University (KTU)
B.Tech · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Tata Insights and Quants, Tata Industries Limited
Data Analytics Intern
October 1, 2025 – April 1, 2026
Bengaluru, Karnataka, India
NanoBit 1-Bit Small Language Model
February 1, 2026 – February 1, 2026
Designed and trained a custom 1-bit SLM architecture with a 50k+ GPT-2 vocabulary using TikToken tokenizer Engineered custom training pipelines for local CPU hardware and optimized inference scripts for lightweight deployment Implemented dual-persona datasets merging veterinary domain knowledge with general conversational parameters
Voice-Enabled AI Agent on Raspberry Pi
January 1, 2024 – January 1, 2024
Built a fully voice-enabled AI agent with persistent memory using LangChain and Whisper for speech recognition Integrated ChromaDB vector database for contextual RAG pipeline enabling long-term memory and task execution Deployed on Raspberry Pi hardware, demonstrating edge AI capability with minimal compute resources
Fake News Detection System
January 1, 2024 – January 1, 2024
Built an end-to-end AI-powered fake news detection platform using Django REST backend and LangChain pipelines Integrated Gemini API for LLM-based reasoning - providing structured classification with contextual explanation, not just a label Designed modular pipeline architecture allowing independent LLM provider swapping without backend changes
Farmer Auction App - AgriTech Hackathon
January 1, 2024 – January 1, 2024
Built a direct farmer-to-buyer auction platform with integrated negotiation chatbot and payment gateway Recognized at Kerala Startup Mission's Rural AgriTech Hackathon (CPCRI)
Learnxt AI-Powered Learning App
January 1, 2023 – January 1, 2023
Built a production mobile app with RAG pipeline using embeddings and LLM APIs for context-aware learning responses Live on Google Play Store
Cultural Fit Analysis
The candidate exhibits a strong passion for AI and innovation, as evidenced by multiple personal projects, hackathon participation, and a leadership role in an innovation cell. The diversity of projects, from edge AI to mobile apps and enterprise data analytics, suggests adaptability and a broad interest in applying technology. This aligns well with a dynamic, research-oriented AI engineering environment. The focus on practical, deployable solutions indicates a results-oriented mindset.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and innovative approach to problem-solving, particularly in developing novel AI solutions. Participation in hackathons and leadership roles suggests teamwork and initiative. The internship experience at Tata Insights and Quants demonstrates an understanding of production workflows and collaboration with engineering teams. However, without direct assessment data, specific soft skills like communication under pressure or conflict resolution cannot be definitively evaluated.