We are looking for exceptional and experienced software engineers to join us in our fast-growing team of data scientists and engineers. You’ll play a central role in the planning and development of our AI-first energy and climate optimization platform and our drive towards unprecedented scale and impact in the fast transition to sustainable energy consumption.

You will focus on either backend or UX engineering, but as part of a small and efficient development team you’ll have the chance to make contributions across the entire stack from infrastructure, data science and backend to UX and data visualizations.

Responsibilities

• Develop high-quality code and architecture

• Responsibility and ownership of features

Skills and expertise

• Experience with software engineering in general and preferably with technologies in our current stack: Python/Django, Postgres, HTML+CSS+Javascript, Redis, Docker, AWS, Linux, Git

• You are a self-starter who enjoys working independently while keeping the team’s common goal in mind

• Fluency in English (Danish is not a requirement for this position)

• Comfortable with asynchronous, written communication

Good to have

• Experience implementing multi-tenant SaaS web applications and APIs

• Experience building data and machine learning based products

Practicalities

Our engineering team works asynchronously and autonomously, guided by our overall company goals. There are no daily standups or strict sprints but a focus on efficient processes that work well for everyone, individually and collectively.

In our technical teams we work from wherever and whenever. You can choose to work from our office in Aarhus, Denmark or remote, aiming for at least 3 hours of overlap with Danish business hours (9-17 CET). Compensation including equity is offered based on qualifications.

About Ento Labs

Our mission is to make it easy and cost-effective to analyse and monitor energy consumption of every building on the planet with scalable machine learning systems and help drive decarbonization of the built environment. 

Building energy use causes around 40% of global greenhouse gas emissions, and are still rising due to slow and expensive energy optimization processes. Using data and machine learning we can solve many of the inefficient steps in the process, including robust identification, prioritization, collaboration, verification and monitoring of energy optimization efforts.

During the past year, we’ve welcomed many public and commercial building owners and partners to our network. We are now covering almost 5000 buildings and 1 TWh of energy consumption. This has already led to large energy and CO2 savings, but we’re just getting started. 

As part of the early team, you will be essential in making our vision reality - we’re very much looking forward to welcoming you on our journey.

Apply today

We review applications on an ongoing basis.