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AI Engineer with 1+ years in ML pipelines, LLM-powered applications & scalable backend systems
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AI Engineer with 1.5 years of software engineering experience at TCS, specializing in building end-to-end ML pipelines, LLM-powered applications, and scalable backend systems. Experienced in developing RAG-based solutions, computer vision models, and production-grade REST APIs using Python, FastAPI, PyTorch, LangChain, and OpenAI APIs. Strong foundation in backend engineering combined with applied AI development. Currently advancing expertise in Agentic AI, fine-tuning techniques, and Hugging Face Transformers.
K. Ramakrishnan College Of Technology
B.E. · Computer Science and Engineering
August 1, 2019 – June 30, 2023
Tata Consultancy Services (TCS)
Java Backend Developer
May 1, 2024 – October 1, 2025
Chennai, Tamil Nadu, India
Car Damage Detection
February 1, 2026 – March 1, 2026
• Built a Computer Vision system using ResNet50 and transfer learning to classify vehicle damage into 6 categories. • Trained on 2000+ labeled images with data augmentation techniques, achieving 80% validation accuracy. • Developed an interactive Streamlit dashboard for real-time image upload, prediction, and confidence scoring. • Integrated model monitoring to track prediction confidence and flag low-certainty inputs for review.
View ProjectPrompt2Site – AI Website Generator
January 1, 2026 – February 1, 2026
• Developed an end-to-end Generative AI website generator producing complete responsive websites in under 5 seconds per request. • Built full-stack architecture using React and FastAPI, reducing manual website development time by 80%. • Applied advanced prompt engineering techniques, improving structured code generation consistency by 90% across test prompts. • Implemented a CI/CD pipeline using GitHub Actions to automatically test and deploy the FastAPI backend after each commit.
View ProjectCredit Risk Modelling
December 1, 2025 – January 1, 2026
• Designed an ML risk analytics system achieving 98% ROC-AUC using XGBoost and SMOTE-Tomek for class imbalance. • Conducted A/B testing of two XGBoost hyperparameter sets via Optuna, achieving over 90% accuracy and 93% recall. • Launched a real-time prediction API with sub-second response time and interpretable tiered risk scoring (Poor-Excellent).
View ProjectHealthcare Premium Prediction
November 1, 2025 – December 1, 2025
• Designed an ML-based healthcare premium prediction system, automating manual estimation and increasing model accuracy to 97%. • Deployed a FastAPI backend integrated with a Streamlit interface, delivering real-time predictions with low-latency response.
View ProjectMaster Machine Learning for Data Science & AI
Codebasics
February 1, 2026 – Present
Artificial Intelligence & Machine Learning
Internshala Trainings
November 1, 2025 – Present
LLM Engineering: Master AI, Large Language Models & Agents
Udemy
September 1, 2025 – Present
Cultural Fit Analysis
The candidate's diverse personal projects in Generative AI, Computer Vision, and traditional ML (Credit Risk, Healthcare Premium) demonstrate a strong passion for AI and continuous learning. The blend of backend development experience with AI project work shows adaptability and a broad technical interest, aligning well with an innovative AI-focused culture. The certifications further underscore a proactive approach to skill development.
Soft Skills & Operational Fit
The candidate's project descriptions highlight collaboration in Agile Scrum cycles and a focus on delivering production-ready features, suggesting good operational fit and teamwork skills. The emphasis on reducing manual effort and improving efficiency across projects indicates a problem-solving mindset.