Full Stack Engineer - Decision OS

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Summary

causaLens are the pioneers of Causal AI — a giant leap in machine intelligence.

We build Causal AI-powered products that are trusted by leading organizations across a wide range of industries. Our Causal AI Platform empowers all types of users to make superior decisions through intuitive user interfaces and apis that adapt to their level of technical expertise. We are creating a world in which humans can trust machines with the greatest challenges in the economy, society, and healthcare.

We are looking for motivated and high-achieving Fullstack Software Engineers, based in London, to join our DecisionOS Product team. In this team you will be building frameworks and applications that allow data scientists and business users to build and extract real business value from causal models.

This is a full-time placement with significant opportunities for growth in a rapidly expanding team.

Roles and Responsibilities

As a Full Stack Engineer, you will be involved with the delivery of features into our product and application framework. You will own the implementation of features from start to finish, all the way to being deployed to our customers. You should have strong technical and communication skills and experience with using SDKs, experience creating SDK’s would be a plus. You will be expected to push forwards your own ideas and contribute to design and architecture discussions.

What You’ll Be Working On

You will be working building AI focused features in our application framework, which will allow data scientists to build amazing applications leveraging their causal models. You will be expected to work across our application stack and be willing to learn any areas which you do not already have experience with. Our primary languages are Python for the backend of the framework and Typescript + React for the web facing front-end. The decisionOS SDK is a tool used by developers and data scientists, so you’d be expected to have familiarity with development practices, package management, running debugging both locally and remotely as well as building images with Docker.