I am a tech-savvy engineer passionate about applying AI and Software Engineering to solve complex real-world problems. Currently pursuing a Master's in Computer Science at North Carolina State University. I work as a Graduate Research Assistant at the STEPS Center, where I develop multi-agent LLM systems for scientific knowledge workflows. My work focuses on building scalable and explainable Retrieval-Augmented Generation (RAG) architectures, incorporating trust, validation, feedback loops, and real-time interfaces. Previously, I contributed to a DARPA-funded research project at CAMAL Labs, where I developed real-time machine learning and computer vision pipelines for additive manufacturing. I built ML-integrated software systems that reduced inference time by 4.3x and improved model accuracy and efficiency by over 70%, supporting first-time-right production of defense-critical components. My journey includes a Bachelor's in Electrical and Computer Engineering from India and an impactful stint as an Applied Scientist Intern at Amazon, where I developed machine learning and GenAI solutions. Additionally, as an Intel IoT Student Ambassador and DeepLearning.AI Event Ambassador, I founded and led the Intel IoT Club, fostering a community of 2000+ members and mentoring a team of 35+ individuals. I am open to internship opportunities in Data Science, Applied Science, Machine Learning, and AI, especially in areas intersecting with Computer Networks, IoT, and Software Development. Let’s connect if you're looking for someone eager to make an impact in these domains. When I am not coding or tinkering with devices, I enjoy cooking, photography, blogging, and music. You can find some of my work on my GitHub profile.