I build production-grade AI systems — LLM & RAG pipelines, computer-vision models, and cloud-native backends. From architecture to deployment, end to end.
I'm an Applied AI & Cloud Engineer working at the intersection of artificial intelligence, backend engineering, and cloud infrastructure. My work spans production LLM systems and real-time computer vision.
At Infosys BPM, I build enterprise GenAI applications — RAG pipelines, multilingual conversational AI, and scalable FastAPI services on Azure. Previously at DRDO-CABS, I built real-time object-detection models for defence aerial surveillance.
I hold an M.Tech in AI & Data Science and I'm driven by taking systems from problem definition through to deployment, monitoring, and optimization — with a growing focus on research and edge AI.
Agentic research platform with federated search across OpenAlex, Semantic Scholar & arXiv, RAG chat with citation grounding, and a personalized research feed.
ML clinical decision-support system for early detection using genetic-algorithm feature selection, XGBoost, and SHAP explainability for interpretable predictions.
U-Net semantic-segmentation model for satellite imagery, improving mIoU by 18% through transfer learning and advanced data-augmentation strategies.
Production-grade RAG system letting enterprises query internal documents through LLMs, with a secure, scalable backend architecture.
Open to GenAI / AI-ML Engineering roles and interesting research collaborations. Reach out — I'd love to talk.