Headline

AI Software Engineer Intern @Intel Corporation || AI Engineer | LLMs | RAG | AI Agents

About

AI Software Engineer with experience in large-scale LLM inference systems, GPU acceleration, AI infrastructure, and full stack AI application development. Currently working at Intel on optimizing high-performance AI systems across Intel and NVIDIA GPU architectures using vLLM, TensorRT, RAG pipelines, and scalable backend workflows. Passionate about building intelligent, scalable, and production-ready AI systems that combine modern software engineering with cutting-edge machine learning. Experienced in developing AI-powered applications, inference optimization pipelines, autonomous agent workflows, semantic search systems, and backend APIs for real-time AI workloads. Skilled in Python, SQL, PyTorch, TensorFlow, CUDA, vLLM, Flask, REST APIs, and GPU-aware system optimization, with hands-on exposure to H100/H200 infrastructure, cloud workflows, and scalable AI deployments. Previously worked on: • LLM inference optimization & agentic AI systems • Retrieval-Augmented Generation (RAG) pipelines • Computer Vision & Biomedical AI research • AI-powered recommendation and prediction systems • IoT + AI assistive technologies • Full stack AI applications and backend services Certified Salesforce AI Specialist with strong interest in Generative AI, AI Infrastructure & Systems, Full Stack AI Engineering, Applied Machine Learning, Autonomous AI Agents and Scalable AI Platforms Always open to collaborating on impactful AI systems, research, and next-generation intelligent applications.

Location

Bengaluru

Work experience

AI Software Engineer at Intel Corporation, Jun 2025 - Jun 2026 · 1 yr 1 mo, Bengaluru, Karnataka, India, Contributed to the development of production-scale Generative AI systems, focusing on LLM inference optimization, GPU acceleration, and agentic AI applications. Built and optimized RAG pipelines, inference services, and backend automation workflows while working with Intel and NVIDIA accelerators. Gained hands-on experience in AI infrastructure, performance engineering, and deploying scalable machine learning systems for real-world use cases.

Data Science Intern at GTechnologies Pty Ltd, Jun 2024 - Feb 2025 · 9 mos, Australia, Worked on AI-driven healthcare solutions involving ECG data interpretation, clinical decision support, and Electronic Medical Record (EMR) integration. Developed and evaluated machine learning models for medical diagnostics, achieving high predictive accuracy while improving model reliability and performance. Applied NLP, deep learning, and cloud-based technologies to support intelligent healthcare workflows and data-driven decision-making. Collaborated on end-to-end AI development, from data preprocessing and model training to deployment and system optimization.

Vice President at E-Cell, VIT Bhopal, 2023 - Mar 2024 · 1 yr 3 mos

Team Leader - Content Team at E-Cell, VIT Bhopal, Feb 2022 - May 2023 · 1 yr 4 mos

Team Member - Content Team at E-Cell, VIT Bhopal, Feb 2021 - Feb 2022 · 1 yr 1 mo

Trainee at CSIR-Central Scientific Instruments Organisation, Jul 2023 - Dec 2023 · 6 mos, Chandigarh, India, Worked as a Machine Learning Research Trainee at CSIR, contributing to biomedical AI research involving computer vision, generative AI, and healthcare analytics. Developed deep learning models for Knee Osteoarthritis detection from medical imaging data and utilized GANs for synthetic thermal image generation. Built and optimized an LLM-powered chatbot while applying TensorFlow and PyTorch to improve model accuracy and inference performance. Collaborated on research-driven projects aimed at advancing AI applications in healthcare and medical diagnostics.

Data Analytics Traineeship at MedTourEasy, Nov 2022 - Dec 2022 · 2 mos, Remote, Completed hands-on working project on "Prediction of Blood Donations."

Education

Master of Technology - MTech, Computer Science, Thapar Institute of Engineering & Technology

Bachelor of Technology - BTech, Computer Science Engineering, Vellore Institute of Technology