Hi, I’m José Guillermo Saldaña Cárdenas
I am a
I am a software engineer, focused on web backend services.
Hi, I’m José Guillermo Saldaña Cárdenas
I am a software engineer, focused on web backend services.
Onboarded to AR/VR development focus area. Was laid off before onboarding a team.
Joined the Ads Manager Incubator team in the Ads SegMob org. Integrated Dynamic Ads, which increase impressions by 20% on average compared to ads built by advertisers, with React.
Part of the Payments EngProd work group, on the Payments Regtest team. Developed validation for testing samples, with Java, that analyzed if critical use cases were covered by regression tests. Onboarded teams to evaluate results of validation, and programmed weekly generated reports on Python. These concluded that, on average, 7% of samples did not cover all critical use cases.
Was part of the Cloud & AI org, on the Azure Policy team. Designed and created new dashboards for customers, using Typescript and SQL-like queries. These dashboards were demoed and, when polled, 75% of customers mentioned an improvement in visibility and the dashboards served as a great initial tool to diagnose problems.
Interned with the Efficient Investigations team in the Data Infra org, developing features for an internal tool that monitors, detects, and analyzes problems in various products and internal tools to inform developers on possible causes. New features reduced wait times of u[ tp 40% of main service by distributing requests with that required specialized processing to more efficient services.
Designed and implemented APIs for different projects in the company, using Node and Express. Pioneered design pattern changes in back-end projects to reduce implementation time by 30% by developing a modular design with independent external services. Systems integration for various 3rd party services.
Developed a chatbot on Dialogflow to answer doubts about the academic model Tec21, a new academic program developed in my university. Used Firebase Firestore and Functions to handle intents via a webhook. Loading times decreased on 25% of intents by optimizing of the database queries.
Renovated Tutorings 24/7, an online code verifier tool used to validate student's code submitted to Data Structures & Computer Algorithms classes. Migrated to AWS with EC2, S3, RDS, and ElastiCache to enable support for more than 500 concurrent active users while keeping costs at a minimum. Fixed various problems both in front and back end, using Angular, Python with Flask, Docker, PostgreSQL, and Redis queues.
Designed and engineered a concept of an extendable fan-referral NFT framework, with Open Zeppelin’s implementation of ERC721. The framework incentivizes token transfers, increasing worth of mouth advertisement for a piece of work, and creates a platform where the creator can reward their most loyal fans, as well as facilitate the creation of a community.
PM for the automatic check-in feature for upcoming ACM-organized hackathon. Project developed using a MEAN stack. It is used in the check in for the event, having an impact the attendees and staff of the event, which sum up to 500 users yearly.
Collaborated with a team to design and implement a web application using Java, JavaScript, HTML and CSS over the course of 10 weeks, leveraging various Google Cloud Platform APIs, including App Engine and Datastore. Learned to create Java Servlets and used Google Maps API on Javascript to create location highlights and ratings, stored in a Datastore database service.
Created a stealth-based first-person shooter using Unity and C#. The game uses sound as its main lighting mechanic. The game is completely dark and everything that makes a sound also emits light, which works to keep the player with limited information as well as keep enemies from spotting you. The game was awarded best student-developed game of the year by video game expo of Tec de Monterrey Campus Monterrey.
Using Amazon Web Services , we created a NodeJS server that used BBVA internal tools to service android apps. Used machine learning algorithms to predict sale peaks from data generated by apps.