Software Engineer, Full-Stack

We are looking for seasoned Full-Stack engineers who love building new products in an iterative and fast-moving environment. In this role, you will build software from the ground up to solve critical bottlenecks for DatologyAI customers and internally. As one of our key hires, you will partner closely with our founders on the direction of our product and drive business-critical technical decisions.

You will contribute to developing the core product that customers use for curating their datasets and the visualizations around it, as well as the internal tooling that our team uses daily to develop the core product. You will have a broad impact on the technology, product, and our company's culture.

As a Software Engineer - Full-Stack at DatologyAI, you will be responsible for:

Own the full product development lifecycle for customer-facing data curation products as well as the new internal infrastructure and product experiences.

Talk to customers and internal stakeholders to understand their problems and design solutions to address them.

Collaborate with a cross-functional team of engineers, researchers, designers, etc to bring new features and research capabilities to our customers.

Ensure that our products and systems are reliable, secure, and worthy of our customers' trust.

There are a few specific things we’ll be looking for that will help you succeed in this role:

Have meaningful experience with leading and building production full-stack and backend experiences that deliver on major product initiatives

Proficiency in JavaScript/TypeScript, React, other web technologies, and Python.

Care deeply about quality, functionality, and the humans we’re communicating to by sweating the details, down to the last page request.

Experience maintaining a high-quality bar for design, correctness, and testing.

Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done.

Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed

Have prior experience in ML/AI (preferred but not required).