The Adobe Platform Team (aka Ethos) is looking for a software engineering intern to work on our cloud efficiency project. Are you interested in Kubernetes, Docker, and writing tools and APIs using node.js? If so, this could be the internship for you!
Ethos deploys Adobe-wide software and infrastructure technology, promoting containerization, clusterization, and continuous integration/continuous deployment (CI/CD). We create tools, processes, and workflows that connect and empower hundreds of internal development teams.
Your role will be to collaborate on the cloud efficiency tooling that empowers our clients to save money on our Kubernetes-based platform. We believe through the scale of Ethos that we can bring meaningful efficiency improvements to all our clients. You will help us build tooling that enables developers to get real-time feedback about their service utilization and make informed configuration changes.
In this role, you will:
- Work on an agile scrum team to complete and iterate rapidly on high-impact features
- Have the opportunity to both design your vision as well as implement it
- Collaborate closely with a small team of engineers
- Experience the full product life cycle, from concept to completion
What you need to succeed:
- Experience writing backend apps using node.js or a similar framework
- Basic understanding of Kubernetes concepts
- Excellent communication skills (we’re a geographically distributed team)
- Good understanding of building and consuming REST APIs
- Experience using git and GitHub
Nice to haves:
- Familiarity with K8s yaml, kubectl, and deploying applications on Kubernetes
- Experience with AWS Lambda and the Serverless framework
- A desire to see a feature through from idea to deployed in production, from user feedback and research to coding designs
- Comfortable with taking the initiative and working independently
- Any open-source contributions
Some of the technologies we work with:
- Git & Github
About the Team
- We’re building the platform to run Adobe’s web, big data, and machine learning services.
- Our team of 40+ people works in smaller groups of 3-5 developers. This allows us to be agile while working as part of a larger organization.
- We’re globally distributed but remain intimate. The group is in India, Romania, New York City, Lehi, Seattle, and San Jose just to name a few.
- Our product and teams are growing quickly. Though we are established, in production, and iterating, there are plenty of challenges to overcome, decisions to be made, and new development to do.