Larbi Boukert

Full Stack Web Developer - React/Next.js/TypeScript | .NET6/ASP.NET Core at Acoustic Wells, Inc.

Larbi Boukert has a strong background in full-stack web development, with expertise in technologies such as React, Next.js, TypeScript, ASP.NET Core, and Node.js.

From October 2019 to March 2020, they worked at Sonatrach as a Full Stack Web Developer, focusing on React and ASP.NET Core.

In March 2020, they joined isefka as a Full Stack Web Developer, responsible for implementing a Figma design into a user-friendly web application. Larbi also created a backend infrastructure for the admin dashboard and integrated third-party APIs such as social logins and cloud storage APIs. Additionally, they refactored a legacy app by restructuring the code and fixing responsiveness issues.

Larbi then joined FullStackLabs in May 2021, where they continued their role as a Full Stack Web Developer, specializing in React, TypeScript, and ASP.NET Core. Larbi worked on various projects until April 2022.

Currently, Larbi is a Full Stack Web Developer at Acoustic Wells, Inc. starting from April 2022. Their focus is on React, Next.js, TypeScript, and .NET Core/ASP.NET Core.

Overall, Larbi Boukert's work experience highlights their expertise in full-stack web development and their ability to adapt to various technologies and project requirements.

Larbi Boukert obtained a Bachelor's degree in Computer Science from Université M'Hamed Bougara de Boumerdes, graduating in 2018. Following this, Larbi pursued further education and completed a Master's degree in Computer Science from the same university, which spanned from 2018 to 2020.

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Dubai, United Arab Emirates

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Acoustic Wells, Inc.

Acoustic Wells offers industrial IoT solutions to maximize oil field efficiency. It uses sensing technologies and proprietary algorithms to reduce environmental impact. It builds an IoT system that can operate and last even in the most remote, toughest conditions. The company helps reduce the need for the painstaking task of daily inspection ofwells while providing operators much more fine-grained, actionable data.


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