Senior Full Stack Engineer (Qondo)

Johannesburg, SOUTH AFRICA Engineering Full-Time

Fullstack Python Django Flask JavaScript React AWS AI SQL NoSQL

Artificial intelligence will define the financial services sector within the next five years, but incumbent institutions cannot adopt artificial intelligence due to two core problems: access to quality training data, and access to high - caliber talent. Neo is building the only full-stack artificial intelligence platform focused on the financial services industry. With a first client already in place, Neo is ready to redefine how banks think about AI
We’re entering the build phase of our start-up journey and we are looking for a Full Stack Software Developer. You will be the first full-stack engineer and will have a critical role in helping to develop overall software engineering infrastructure and best practices for an always-on deployment environment and work within the Neo team to build a SAAS platform product from the ground up.

Responsibilities

Design and build a high-performance web application based on restful APIs
Work with UI designers to implement front-end technologies
Architect and implement software libraries
Develop software devops engineering processes (design, build, quality, maintenance)
Note: Responsibilities will grow and evolve based on your interests, capabilities and client needs.

Experience - Required Skills

Bachelor’s degree in Computer Science, Engineering, or related technical field
5+ years experience with Python web server frameworks (Django or Flask)
5+ years experience with React JS and JavaScript (preferably NodeJS, ExpressJS)
Demonstrable experience of developing professional software from concept to distribution
Strong knowledge and experience of developing with cloud services (AWS, GCP, or Azure)
Passion for engineering products, technology and AI

Experience - Preferred Skills

Experience with Git version control and Docker
Experience with SQL and NoSQL databases and data modeling
Experience with AI tools, libraries, and languages (TensorFlow, PyTorch, Spark, SageMaker, Scikit-learn, NLP, spaCy, etc)
Good understanding of how to leverage available cloud base services and existing machine learning platforms such as AWS SageMaker using Tensorflow or Google AutoML to avoid reinventing the wheel.

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