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AI Engineer with 3+ years in LLMs, Generative AI & RAG architectures.
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Assessing your cultural and operational fit
Innovative AI/ML Engineer and Computer Science graduate with a strong focus on Large Language Models (LLMs), Generative AI, and RAG architectures. Proven track record in developing high-precision AI solutions, including domain-specific NL-to-SQL translators and automated document intelligence systems. Experienced in deploying local LLMs and building agentic workflows to solve complex industrial data challenges. Passionate about applying AI and machine learning to develop scalable, real-world solutions.
Jeppiaar Engineering College
Bachelor of Engineering · Computer Science
N/A – June 30, 2026
SightSpectrum Pvt Ltd
AI Automation Intern
January 1, 2026 – April 1, 2026
Chennai, Tamil Nadu, India
Altruisty Innovation Pvt Ltd
Full Stack Development Intern
September 1, 2025 – Present
Chennai, Tamil Nadu, India
InTrAinZ
Machine Learning Intern
October 1, 2023 – Present
India
High-Fidelity Local RAG-based Document Intelligence
June 1, 2025 – June 1, 2026
• Developed a High-Fidelity Local RAG-based Document Intelligence System using Python, Gemma 3 via Ollama, LangChain, and ChromaDB for secure AI-powered querying of confidential documents in a fully local environment. • Implemented semantic search, vector embeddings, document chunking, and an interactive AI assistant using Chainlit to improve contextual understanding, response accuracy, and enterprise knowledge retrieval by approximately 70% while ensuring complete data privacy.
AI-Powered Early Career Skill Gap Analyzer
June 1, 2025 – June 1, 2026
• Developed an AI-Powered Early Career Skill Gap Analyzer using Python, NLP, Sentence-BERT (SBERT), and Cosine Similarity to analyze resume-job role alignment and identify semantic skill gaps beyond traditional keyword-based matching. • Implemented a Retrieval-Augmented Generation (RAG) workflow to generate personalized 30-day learning roadmaps, enabling users to understand strengths, improve missing skills, and enhance career readiness through AI-driven career intelligence.
SCM-Query: Domain-Specific NL-to-SQL using LoRA
June 1, 2025 – June 1, 2026
• Developed SCM-Query, a domain-specific NL-to-SQL engine using Python and Qwen3:4b to translate natural language queries into valid SQL statements for Supply Chain Management databases. • Fine-tuned the model using LoRA (Low-Rank Adaptation) with float16 optimization for efficient low-VRAM inference, and evaluated performance using Exact Match (EM) and F1 Score metrics on complex SQL constructs including CTEs and Window Functions.
G-Pay Fraud Transaction Detection
June 1, 2025 – June 1, 2026
• Developed a G-Pay Fraud Transaction Detection System using Python and the Random Forest algorithm to classify fraudulent and legitimate digital payment transactions with improved detection accuracy. • Performed data preprocessing, feature selection, and imbalanced data handling, and evaluated model performance using Accuracy, Precision, Recall, and F1-Score to identify anomalies in high-volume transaction datasets.
AI Fundamentals
IBM SkillBuild
January 1, 2025 – Present
AI Basics Certification
Infosys Springboard
January 1, 2025 – Present
FullStack Web Development Mini Project Certification
Unknown
January 1, 2025 – Present
Python for Data Science Elite Certification
NPTEL
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's project portfolio is diverse, covering RAG, NLP, LLM fine-tuning, and traditional ML, which aligns well with the breadth often sought in AI engineering roles. The focus on practical, problem-solving AI applications (e.g., secure document intelligence, fraud detection, skill gap analysis) indicates a results-oriented mindset. The internships, including an AI Automation role and a Full Stack Development role, suggest a willingness to learn and contribute across different technical areas. The candidate's academic background in Computer Science and various AI/ML certifications further support a strong interest and commitment to the field. The personal projects demonstrate initiative and self-driven learning, which are positive indicators for cultural fit in an innovative environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and problem-solving approach, focusing on real-world applications and measurable improvements (e.g., 'improve contextual understanding, response accuracy, and enterprise knowledge retrieval by approximately 70%'). The diverse range of projects, including secure document intelligence, skill gap analysis, and NL-to-SQL, suggests adaptability and a strong interest in applying AI to various domains. The internship experience, particularly the AI Automation Intern role, shows an ability to work on structured projects and deliver solutions within a company context. However, without direct interview data, assessing collaboration, stress handling, and communication in a team setting is limited.