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AI Engineer with less than a year in LLM application and RAG pipeline development
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 B.E. Computer Science student with hands-on experience in building AI applications, LLM-powered pipelines. Proficient in Python, LangChain, RAG architectures, and REST APIs. Experienced in deploying end-to-end AI products including an AI Interview Analyzer and a multi-model RAG chatbot. Passionate about the societal impact of AI in India across education, healthcare. Actively seeking AI Engineer, Python Developer, or Software Developer roles.
K. Ramakrishnan College of Technology, Trichy
B.E. · Computer Science & Engineering
August 1, 2022 – April 1, 2026
AI Interview Analyzer
June 24, 2026 – Present
Built a real-time interview analysis tool that assesses body language, speech clarity, and content quality using computer vision and NLP. Integrated MediaPipe for pose and facial expression detection; used Whisper for speech-to-text transcription. Presented at AI Tinkerers Trichy Demo Day to an audience of AI practitioners and startup founders.
RAG Chatbot (LangChain + ChromaDB + Groq)
June 24, 2026 – Present
Designed and deployed a Retrieval-Augmented Generation pipeline using all-MiniLM-L6-v2 embeddings and Groq's llama-3.1-8b-instant LLM. Implemented document ingestion, chunking, vector storage, and multi-turn conversational memory via st.session_state. Debugged end-to-end pipeline including .env encoding issues, API key configuration, and ChromaDB persistence.
Sentiment Analysis API
June 24, 2026 – Present
Developed a production-ready sentiment analysis REST API using a fine-tuned DistilBERT model. Containerized with Docker and documented endpoints via Postman for portfolio demonstration.
Google for Developers Machine Learning course-Completed
Google for Developers
June 1, 2026 – Present
AWS MachineLearning Crash course-Completed
AWS
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's passion for the societal impact of AI in India across education and healthcare suggests alignment with mission-driven organizations. The diversity of projects (interview analysis, RAG chatbot, sentiment analysis) indicates a broad interest in AI applications. However, the lack of team-based projects or professional experience makes a comprehensive cultural fit assessment challenging.
Soft Skills & Operational Fit
The candidate demonstrates initiative and a proactive approach through personal projects and presentations. The project descriptions indicate an ability to debug complex issues and a focus on practical application. However, without formal work experience or psychometric test results, it's difficult to fully assess operational fit, teamwork, and stress handling capabilities.