Past Performance
Tripoint Solutions for the National Institutes of Health, 07/2020-present,
In addition to providing e-GOS application modernization and migration to AWS Cloud, we also provide security, database and system architecture and administration, and work with NITAAC to define application functionality and translate them into application features. This includes extending e-GOS application platform to support SP4 GWAC.
Metro Star Systems for the National Institutes of Health, 09/2016-07/2022,
Responsible for AWS Systems Architecture, setup and configuration and DevOps activities for e-GOS. Perform database and application systems migration duties, including capacity planning, installation, configuration, database design, data migration, performance monitoring, Continuous Integration and Deployment and Operation. Data Analytics, Reporting and Big Data Implementation using AWS services.Metrics: Platform is composed of 5 environments (DEV, QA, UAT, DEMO, PRO) using 4 tiers architecture: front end with Angular JS, back end with Spring-Hibernate, Data layer with MS SQL and integration tier with Apache SOLR. Production and UAT environments are composed of a cluster or servers which sit behind AWS Elastic Load Balancers (ELB) using auto scaling groups to scale up or down based on traffic or load. The database is composed of about 120 tables, 470 triggers and over 10 millions of records
Code Creator LLC, 2/3/2020 – 10/31/2022,
Supported the design and implementation of serverless SaaS application allowing user to upload and store text, media and various file types and extract them into a variety of AWS AI services such as Textract, Transcribe, and Fraud Detection. Business Value: The platform streamlines documents processing and contributes to business processes automation for documents forms ranging from contracts, taxes, sales orders, insurance claims, and much more.
SEI for Electric Power Research Institute (EPRI), 09/2022-11/2022,
Re-architect and re-engineer a software using Monte Carlo simulation methods to predict the potential crack formation, leak and rupture probabilities for piping and welds used in nuclear reactors. This work is being performed on behalf of the Electric Power Research Institute (EPRI). Programing language includes Fortran and Python.
