Experienced developer with a strong background in automation and web development. Skilled in designing scalable and reliable solutions for complex systems, aiming to contribute effectively to impactful projects.
Overview
4
4
years of professional experience
1
1
Certification
Work History
Automation Developer
Tejas Networks Limited
04.2023 - Current
Framework Development: Co-led the design and development of the Saspy framework, enhancing test case execution efficiency through customized integration with Netmiko, Spirent HLTAPI, Jenkins, and Unittest.
Protocol Testing Automation: Led a three-member team of interns to automate L3 protocols of BGP, OSPF, and MPLS.
Dashboard: created a dashboard that reflected the quality of software using Next.js, FastAPI, MongoDB, and Recharts.
PMS app bug fixes: fixed bugs in the PMS infrastructure, which is built using PHP and MySQL database.
Automated various manual processes and integration to mail alerts, like build upgrades, device crash reports, restore backups, etc.
Used the Pandas library to manage and update large Excel files, thereby reducing human efforts.
Full Stack Web Developer
STL Digital
11.2021 - 03.2023
Created a web app for the client using Next.js and FastAPI.
Collaborated with other developers on code reviews, bug fixes, and feature development.
Contributed ideas towards improving usability of web application interfaces.
Managed both back-end and front-end aspects of development process.
Used Uizard to develop the workflow of the application.
Conducted L1 interviews of the candidates for frontend positions.
Core competencies: DS and algorithms, networking, machine learning, and deep learning
Tools and platforms: Visual Studio, Jira, Bugzilla, Wireshark, MobaXterm, Git
Soft skills: communication, teamwork, problem solving, responsibility, flexibility
Communication Technologies: BGP, OSPF, MPLS, 3GPP, LTE, 5G,5g
Projects
Hospital management system: Created a web app using the Django REST framework for the backend, Next.js for the front end, and MySQL database where patients can book appointments for available slots, and doctors can check their slots for patients of the day
Deep learning: Created an image classifier using the CNN of the Keras library, which can classify 10 classes with an accuracy of 93%, and a user interface using Flask, where the user can input an image and the output is a class