At cost optimization team, our day is usually full of challenges. Have you ever encountered the situation where you need to expand your cloud infrastructure, in order for certain workloads to be deployed, and once the demand is low, to cut back on your cloud spendings? Most of us probably did, or at least know the many paths that need to be taken in order to achieve that.

One of the team's responsibilities is to make sure that whenever a customer is about to deploy something the burden of making sure that things are running & not costing unnecessary money is uplifted from them. These are just couple small pieces of a bigger puzzle. To get into a more detailed perspective, try to answer the following questions:

• What happens when the demand for resources decreases? What should we do?
• What kind of instance types to use (spot vs on-demand)?
• What to do when cloud provider claims all of the spot instances back? Can we predict that?
• What is the most efficient way to handle all of the workloads while taking into account both cost & efficiency metrics?
• What is the visibility of all of the decisions that our engine is taking to both our customers and us?

These are just several of the many questions that are part of the daily job when working in this team.

Being part of this team would involve design and decision-making end-to-end while collaborating with colleagues from other teams. CAST AI being a technical product, it is encouraged, not only to go and code something as written in the JIRA ticket but also to come up with new features & potential solutions to the problems that customers are facing. 

• GoLang is our main language, while Python is an accepted alternative or some of the cases
• Kubernetes which our product is evolving around
• AWS, GCP, and Azure cloud providers, which are currently supported in our platform
• PostgreSQL and Cloud Object Storage for persistence
• GCP Pub/Sub for messaging
• gRPC for internal communication
• REST for public APIs
• We use GitLab CI with ArgoCD as our GitOps CD engine
• Prometheus, Grafana, Loki, and Tempo for observability.

• You have to be physically in any of the European countries GMT 0 to GMT +3
• Strong software engineering skills
• Strong English skills
• Strong verbal and written communications skills
• Ability to work independently or with a group
• A “yes we can” attitude.

• Team of highly skilled professionals to work with and learn from
• Impact and visibility. We’re still a relatively small company, every contribution counts
• Flat hierarchy. Getting in touch with the CEO, CTO, and all the other people from CAST AI team is not only possible but encouraged
• Short feedback loop. We are customer-oriented so that we ship our code changes fast in order to get customer feedback right away
• Flexible working location and hours
• Monthly salary from €6000 to €8000 (gross) depending on the level of experience
• Skin in the game. Every engineering member gets stock options of the company
• Focus time: minimum overhead of meetings, bureaucracy &, etc.
• 10% self-improvement time for personal projects.