Why CAST AI? CAST AI is the leading Kubernetes cost optimization platform for AWS, GCP and Azure customers. The company is on a mission to deliver a fully automated Kubernetes experience. What’s unique about CAST AI is that its platform goes beyond monitoring clusters and making recommendations; it utilizes advanced machine learning algorithms to analyze and automatically optimize clusters, saving customers 50% or more on their cloud spend, improving performance and reliability, and boosting DevOps and engineering productivity. To date, the company has raised $73M from investors including Cota Capital, Creandum, Uncorrelated Ventures, and Vintage Investment Partners. CAST AI has more than 120 employees globally and is headquartered in Miami, Florida. However, this is merely the beginning. Our product roadmap is filled with exciting innovations that are yet to come. We are searching for intelligent, motivated, and self-reliant people to help us fulfill this ambitious mission. These are the core values that hold us all together: DEVELOP AND HIRE THE BEST: Be curious and improve continuously to foster personal development and professional growth. LEAD: Take ownership, never kick the can, and drive things forward in a full-power mode. The company is in your hands. EXPECT AND ADVOCATE CHANGE: Constantly welcome new ideas and opinions. Share insights responsibly with unwavering openness, honesty, and respect. PRACTICE CUSTOMER OBSESSION: The customer always, always, always comes first. Solve the customer’s problem, be open to feedback, act on it, and the rest will follow. What does Kube Team do? The Kube Team serves as the bedrock upon which our cost optimisation product suite rests. Customers initiate their experience with cost optimisation productthrough the infrastructure and solutions constructed by this team. Additionally, the CAST AI Optimisation Engine leverages these foundational elements to realise significant AAA savings for our clients. To give you a glimpse into the complexities we navigate: We’ve successfully engineered ways to integrate independent Kubernetes nodes into existing third-party clusters like EKS, GKE, and AKS. Given the absence of official documentation, this required a good deal of reverse engineering and yielded invaluable insights. We have authored our own Terraform provider. We developed a highly parallelised engine capable of managing and reconciling the diverse clusters of our numerous customers. We’ve implemented a unified API that abstracts away the differing implementations across various cloud providers We’re SME of lower level infrastructure (operating systems, cloud networking, storage and virtualisation)at CAST AI. The above examples merely scratch the surface of what we’ve achieved. Consider that these efforts are magnified by the range of cloud providers we support -and each one presents its own unique challenges. Each development sprint uncovers new hurdles and learning opportunities. We consider ourselves fortunate to operate in a cutting edge technological landscape. How Do We Operate? At CAST AI, we specifically seek out Software Engineers rather than Software Developers. This distinction is not merely semantic; it underscores a profound difference in responsibilities and expectations. Let’s delve into what sets the two apart. A Software Engineer is responsible for overseeing the entire lifecycle of a system, starting from its conceptual genesis to its continuous delivery of value to customers. When a high-value feature is identified and properly prioritized, an engineer takes ownership. The task entails not just coding but also meticulously reviewing the technical architecture, design, and feasibility of the feature. Beyond functional aspects, we pay heed to: Testability Adaptability Performance and Scalability Deployment and Compatibility Debugging and Operational Management Throughout this comprehensive process, collaboration is key. While engineers are accountable for end-to-end delivery, they are also encouraged to consult with peers to arrive at the most effective solutions. The capacity to work both independently and as part of a team is essential. To expedite delivery, we have devised a suite of proprietary tools that assist us in various aspects of development. Engineers periodically switch roles to write automated end-to-end tests, optimise our GitOps-enabled continuous integration and continuous deployment (CI/CD) pipelines, or fine-tune our observability stack. We even have a rotation for passive on-call duties to promptly address any issues that arise within our codebase. It’s worth noting that we do not employ separate DevOps or QA roles within our engineering team. Self-reliance is vital: we automate everything and construct our own tooling. Therefore, a broad systems-oriented perspective – going beyond mere software development – is indispensable for success within our team. Our mantra is straightforward: we build it, we test it, we ship it and we operate it. Here are some of the tools we use daily: GoLang is our language. Kubernetes is our core product. AWS , GCP, and Azure are the clouds we operate. Postgres and cloud object storage for persistence. Terraform for IaC. GCP PubSub for messaging. GRPC and REST APIs. We use GitLab CI with ArgoCD as our GitOps CD engine. Prometheus , Grafana , Loki, and Tempo for observability. Deployment charts are written in Helm. Having experience with these tools is not a strict prerequisite for the ideal candidate, but it does offer a competitive edge. Requirements: 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 What’s in it for you? Team of highly skilled professionals to work with and learn from. Impact and visibility. Every feature engineers develop is being seen and recognised. Short feedback loop. We have an obsession with customer satisfaction. We ship features fast and get instant feedback. Feature projects tend to be completed in 2 to 4 weeks, depending on the scope. Monthly salary from €6000 to €8000 (gross) depending on the level of experience. Flexible working location and hours. We deliver instead of sitting in the office from 8 to 5. Performance reviews every 6 months which ensure that engineer’s compensation is inline with the value created. Skin in the game. Every engineering member gets a share of the company. Time to focus on work with a minimum overhead of meetings, bureaucracy, etc. 10% time to focus on self-improvement or personal projects. Congrats You made it to the end of the post! If you feel excited – get on board! #J-18808-Ljbffr
GitLab API kubernetes-helm loki Terraform Amazon Web Services (AWS) Azure argocd DevOps Prometheus Google Cloud Platform (GCP) Kubernetes Machine Learning Engineering Grafana Software Engineer