Teams at JPMorganChase

Leads the design, experimentation, evaluation, and productionization of machine learning, deep learning, NLP, LLM, and generative AI solutions. Develops production-ready Python code, optimizes model performance, integrates generative AI into ML platforms, and partners with product and engineering teams. Provides technical leadership, mentors practitioners, and drives scalable, measurable solutions using advanced techniques such as fine-tuning, embeddings, RAG, prompt engineering, and distributed training.

Leads development of full-stack, cloud-native software using Java, Python, and AWS. Builds secure microservices, APIs, and LLM-powered capabilities; establishes engineering, testing, reliability, observability, and CI/CD standards; mentors engineers; drives responsible AI-assisted development; and manages production operations, incident response, and technical direction across agile initiatives.

Lead end-to-end delivery of cloud-native, full-stack software initiatives, defining architecture, engineering standards, reliability practices, observability, CI/CD, and secure production operations. Build microservices, APIs, and AI capabilities using LLMs and generative AI. Guide responsible AI-assisted development, lead incident response and continuous improvement, mentor engineers, and align technical priorities across stakeholders and initiatives.