As a Founding Software Engineer with a focus on Wealth Management & Tools at Nomad AI, your primary responsibility will be to contribute to the development and maintenance of mission-critical systems that help tackle problems in SMB wealth management, using software tools such as AWS, NextJS and python. You will work closely with the team and clients to address high-impact, real-world challenges in the financial domain.
Enhanced Technical Expertise and Responsibilities:Data Engineering: You will be responsible for designing, building, and maintaining ETL/ELT processes, data models, and data warehouses using Mage AI and other big data tools.
Data Analytics: You will collaborate with data scientists and analysts to develop and implement predictive models, statistical analyses, and machine learning algorithms using Mage AI and AWS tools.
Advanced Technology Exposure: Our systems incorporate cutting-edge technologies and tools available on the AWS platform, including database, search, inter-process communication, micro-services, vertical scaling, batch scheduling, and more, in conjunction with AWS's data warehousing capabilities.
Designing, building, and maintaining data pipelines, analytics, and reporting solutions using Snowflake and AWS tools.
Collaborating with data scientists and analysts to develop and implement predictive models, statistical analyses, and machine learning algorithms using NextJS and AWS tools.
Developing and maintaining ETL/ELT processes, data models, and data warehouses using AWS and other big data tools.
Skills Required
- Experience with Next.js
- Experience with AWS
- Experience with big data tools
- Experience designing, building, and maintaining data pipelines
- Experience with Snowflake and AWS data tools
- Experience developing ETL/ELT processes, data models, and data warehouses
- Experience collaborating on predictive models, statistical analyses, and machine learning algorithms
What We Do
Nomad AI is a Kyoto-based software company founded by former Kyoto University artificial-intelligence PhD students. It develops iOS and Android applications that use powerful on-device machine-learning algorithms, enabling capabilities such as text detection, natural-language processing, and music-chord recognition. Its platform supports publishing applications to the App Store and Google Play, with a focus on fast, offline experiences and practical on-device AI.
