Backend Engineer @Toptal Core Team (Jan 2022 - Continued)

Maintaining and implement new code in Ruby on Rails classified feature of the company.

CTO @SpicoTech LLC (Dec 2019 - Continued)

Managing technical things

Senior Solutions Architect @UNATION (May 2021 - Jan 2022)

Managing the Ruby and Padrino codes of the company

Principal Software Engineer @Mailmunch (Aug 2019 - May 2021)

Managed the Backend Ruby on Rails with extensive background jobs using Sidekiq multi-threaded systems. Managed the integration with around 15 third party apps including Shopify, Wix, and Mailchimp. Also, do some conversion of front-end APIs from Rails to NodeJS GraphQL.

Chief Technology Officer @GoGhoom (Jun 2018 - Aug 2019)

Making the product from the ground up with Ruby on Rails APIs and VueJS front-end with Dev-Ops and managing the server-side requirements and deliverability. Making UX for User panels, Admin Panels, CSR Panels, Payment Gateways, Order Handling with SMS, Emails and In-App Notifications.

Web Team Lead @myZindagi (Dec 2017 - Aug 2018)

Designing and managing back-end Ruby on Rails based Grape APIs of myZindagi with the features including fat model thin controllers, JSON responses and SMS prescription and image prescription.

Manager (Web Applications) @Pantera Pvt. Ltd. (Aug 2016 - Dec 2017)

Managing Web Applications Front and Backend projects

Software Engineer ROR @Alchemative (Feb 2016 - Aug 2016)

Designing of back-end Ruby on Rails based REST APIs with the features including token based authentications, multi-tenancy, multiple email account and creating full separate front end AngularJS apps that talk with the APIs. I have made complex apps like Customer Management System and Human Resources Management System that has helped me to learn a lot in web development field.

Researcher @Universita degli Studi di Genova (May 2014 - Jan 2016)

Modelling and designing the emotion detection method for agents in crowd by measuring the behavioural changes in crowd in real time. Making a Crowd Simulator and designing behavioural agents in crowd that respond to different situations such as normal, busy and emergency scenarios. Crowd simulator is made in agile so it is easy to change for any kind of scenario and layout to simulate the crowd.

Crowd emotion detection is based on probabilistic graphical model based machine learning so machine learning method can be used anywhere for logical reasoning and automatic responses. Right now, I am working on panic behaviour simulation design in agents to simulate an emergency scenario to understand how crowd behaves in panic.

Embedded System Developer @Powersoft19 (Sep 2013 - Apr 2014)