Joy Mukerjee

Background

About Joy Mukerjee

I’m a systems thinker with a passion for building AI that makes sense—literally and figuratively. My career has spanned energy consulting, enterprise IT, and healthcare tech, but a common thread has been my drive to solve complex, real-world problems through intelligent systems that are explainable, adaptive, and grounded in data. Starting out in energy management, I transitioned into full-stack enterprise application development, then moved into healthcare IT—where I've led platform-level work across data engineering and AI enablement. Today, I’m part of a core platform engineering team developing a GenAI Platform-as-a-Service, where we build agentic and swarm-based AI architectures that orchestrate large language models across workflows with precision and transparency. I hold a Master's degree in Data Science and Engineering from BITS Pilani, and a Bachelor's in Electronics and Instrumentation Engineering. My academic foundation supports my current focus on advanced machine learning systems, where I work hands-on with: • Deep learning and applied ML across domains • LLM fine-tuning, retrieval-augmented generation (RAG), and performance optimization • Prompt engineering techniques for task-specific model behavior • Multimodal learning, particularly in aligning vision, language, and structured data • XAI methods, with an emphasis on interpretability, robustness, and ethical design My research interests center on Explainable AI (XAI), agent-based AI systems, and multimodal deep learning—areas where I blend practical engineering with deep exploration. I’m inherently driven by opportunities to collaborate with research labs or academic institutions that value curiosity, technical depth, and real-world impact. If you’re working at the edge of intelligent systems and believe AI should be both powerful and interpretable, I’d love to connect.