FineTune is seeking a full stack developer with strong hands on experience on React.js, Axios, React-Apollo, GraphQL, Python, Flask/Django, Pytest, Docker, database performance and microservices. S/he must have experience working with at least 3 production released software projects/products that they have deployed on AWS or Google Cloud and working for at least 10 years releasing production quality software.
S/he should be hands on tech and comfortable solving complex system problems while making sure software team understands clearly what they are building, while refactoring/architecting new and existing services to scale to support 5 million users.
You should have hands on experience in optimizing front end code performance, analyzing API caching errors, comfortable digging into docker containers and be diving into large code bases to refactor components and migrate database models.
S/he should also be comfortable interacting with customer and provide guidance on the technical feasibility and scope of engineering/rearchitecting needed to solve problems and deliver features. Full stack developer will also work with QA team to find best ways to increase the performance of the development team and enhance software quality and development speed.
S/he will interface with engineering leadership to continuously drive innovation and new product development while promoting and advancing the scalability and modularization of current platform we are working on with Collegeboard and other partners. S/he will be essential member of the engineering team to drive company vision and mission while scaling the software for larger audience.
Experiences necessary to be successful:
About FineTune Learning
We are working on a variety of projects from componentizing and enhancing front end React.js to optimize user experience and reusability of components. We are constantly collecting data on users to help recommend better resources for their learning. We build interesting but simple dashboards that may help teachers become more data driven. We work on behavioral experiments via randomized control trial through our software.
Our backend is mostly Python/SQLalchemy and supports GraphQL and diverse set of databases depending on the application. Continuous integration and continuous deployment are next in our pipeline. We are facing challenges in scalability and automation which we plan to tackle in 2018 and refactor code to increase the software performance and support 5 million users. We work with our design team to make this experience engaging for effective learning. We practice agile and scrum and strive to continuously improve.