Participating in the elaboration, architecture, design, development, testing, deployment, operation, maintenance, and enhancement of tools, libraries, frameworks, platform and full stack software solutions;
Designing, implementing and operating friendly and scalable APIs and micro services;
Collaborating with the Machine Learning research group to productize the models and research findings as well as maintain AI models deployed in production;
Working on both the backend and front-end aspects of complex solutions;
Participating in the evaluation and selection of the appropriate technology platform, frameworks and deployment architecture for each given problem to solve;
Embracing and promoting Continuous Delivery, Test Driven Development, AI and UX First approach, iterative development (YAGNI) and other SaaS best practices and principles;
Fostering a strong DevOps culture;
Participating in the continuous improvement of development and delivery best practices.
- At least 5 years of experience on large scale projects, preferably continuously delivered SaaS projects.
- An open mind and a desire to learn and use the best language/technology to solve a given problem;
- Experience developing and delivering on a public cloud provider like Google Cloud Platform, Microsoft Azure or Amazon Web Services; or have built an in-house cloud with all that this involves in terms of tools, monitoring, diagnostic, etc.;
- Experience or knowledge of Web GUI frameworks like Angular, React, ExtJS, Backbone, etc. as well as HTML and CSS; Experience with Continuous Delivery of cloud native, microservice-based large scale solutions in a DevOps culture;
- Experience with and belief in TDD and the testing tools for the different portions of the technology stack;
- Experience with Continuous Delivery and its toolchain (e.g. Git workflow, CI systems like Jenkins, CircleCI, SnapCI, Team Foundation, jFrog Artifactory, etc);
- Experience with Docker, Kubernetes or other container-based deployment along with the automation tools;