Abhishek Hegde

I am a Generative AI and AI/ML Engineer with over 4 years of experience designing, developing, and deploying production-grade AI solutions. My expertise includes Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), NLP, Computer Vision, semantic search, and enterprise AI systems. I have built scalable AI applications using Azure OpenAI, LangChain, FastAPI, Python, and vector databases, delivering measurable business impact across semiconductor, healthcare, and enterprise intelligence domains.|
At Accenture, I have architected end-to-end GenAI solutions, including enterprise chatbots, CXO intelligence platforms, semantic search systems, and AI-powered APIs. My work has improved operational efficiency by up to 95%, achieved 98% query accuracy, enhanced healthcare query performance by 70%, and reduced semiconductor defects through computer vision and synthetic data generation. I have also optimized LLM pipelines for better throughput, token efficiency, and scalability while building production-ready ML services.

I hold a Master's degree in Data Science (NLP & Deep Learning) from the University of Arizona and a Bachelor's degree in Information Science Engineering. I am passionate about staying at the forefront of Generative AI, exploring agentic AI systems, multimodal AI, advanced RAG architectures, and LLM optimization techniques.

I enjoy solving complex engineering challenges, collaborating with cross-functional teams, and building AI products that create measurable business value. I am currently seeking opportunities to contribute to innovative organizations where I can leverage my expertise in Generative AI, scalable ML systems, and enterprise AI to solve real-world problems while continuing to grow as an AI engineer.