About

Jayant Jain is a skilled Software Developer with over 2 years of relevant experience in the industry. Currently working at Adobe as a Member of Technical Staff (SDE), he is a part of the security team that develops tools and dashboard for Document Cloud, Creative Cloud, and PPBU business units. He is passionate about solving intellectually challenging problems and has a strong background in Java, Spring Boot, CI/CD, ML, Docker, Jenkins, Backend, Spring, and Python. Jayant has led the agile development of new features through staging environments and facilitated integration with existing Java code by employing Git branching and merging best practices. He has worked on the SpringBoot backend devising a low latency single-view dashboard with 99% accuracy that helps senior leadership make informed decisions about security vulnerabilities in their division. Jayant has also dockerized and added features in existing major security projects, developed, and tested jobs with CI/CD pipelines via Jenkins. Jayant has collaborated with global counterparts to build a common Dashboard platform for metrics visualization and analytics, working on data at scale. His tech stack includes Java SpringBoot, Python, Docker, and PowerBI. Prior to joining Adobe, Jayant worked as an Associate Software Developer at Publicis Sapient, where he underwent intensive training in tools like Java, Spring Framework, and developed and tested 2 microservices of the stock exchange portal group project in a team of 4 while collaborating with other teams on requirements and documenting on Confluence with iterative feedback and following Scrum Agile methodology. Jayant has also worked as an Undergraduate Student Researcher at SBILab, where he developed an interpretable AI model on ECG data aimed at finding HRV features that get altered in COVID-recovered vs healthy subjects. He computed key ECG attributes for classification based on SHAP & LIME plots using Python and constantly consulted with three senior doctors from two major hospitals of Delhi to validate the medical feasibility of the approach. Jayant has implemented machine learning models (MLP, SVM, XGBoost, CatBoost, etc.) for predicting healthy or post-COVID subjects by exploiting various time & freq. domain features extracted from 12 lead ECG data. He has presented the paper at the 2021 IEEE BioSMART conference in Paris. Jayant holds a Bachelor of Technology degree from IIIT Delhi, majoring in ECE, with CS & Finance electives. He also completed his CBSE from Mira Model High School. Jayant is a skilled