Cast AI
cloud cost and performance optimization
Kubernetes optimization platform for reliability and performance. CAST AI uses SLO signals to take guardrailed actions in production.
Sedang merekrut
Apakah Cast AI merekrut?
Ya. Per 8 Oktober 2026, Cast AI memiliki 31 posisi terbuka di Metaintro. 22 posisi diposting dalam 30 hari terakhir.
Lowongan terbuka
Terbaru lebih dulu. Gaji ditampilkan jika dicantumkan di lowongan.
- Senior Software Engineer | Kimchi (API Platform Team)PengembangJarak jauh · €6.5K – €9K/yr—Jarak jauh€6.5K – €9K/yr6 h lalu
- Senior Software Engineer | Kubernetes AutomationPengembangJarak jauh · €6.5K – €9K/yr—Jarak jauh€6.5K – €9K/yr6 h lalu
- Senior Software Engineer | Kimchi (Harness Team)PengembangJarak jauh · €6.5K – €9K/yr—Jarak jauh€6.5K – €9K/yr6 h lalu
- VP MarketingPemasaranEmea · Jarak jauhEmeaJarak jauh—6 h lalu
- Senior Software Engineer | Kimchi (Agent Platform Team)PengembangJarak jauh · €6.5K – €9K/yr—Jarak jauh€6.5K – €9K/yr6 h lalu
- Senior Product Designer | Kimchi | EuropeDesainJarak jauh · €4.5K – €7K/yr—Jarak jauh€4.5K – €7K/yr8 h lalu
- Senior Software Engineer | Platform EngineeringDevOpsJarak jauh · €6.5K – €9K/mo—Jarak jauh€6.5K – €9K/mo9 h lalu
- Senior Software Engineer | Product FoundationsPengembangThe Hague · Jarak jauh · €6.5K – €9K/yrThe HagueJarak jauh€6.5K – €9K/yr9 h lalu
Pola perekrutan
Seberapa cepat Cast AI menambah lowongan, dan bagaimana pengaturan kerjanya.
Lowongan baru tiap bulanLowongan yang pertama kali diposting pada bulan tersebut
Pengaturan kerja lowonganPorsi dari lowongan terbuka
Pelanggan
4 perusahaan yang disebut Cast AI sebagai pelanggannya.
Kata pelanggan mereka
Kutipan dari orang-orang di perusahaan pelanggan Cast AI.
“We run different applications and scale them down during the night. Once done, we use Cast ’s rebalancing to save money in clusters across all of our environments,”
“When I introduced Cast AI, I noticed that when I created my pods, the newly created infrastructure was based on the exact requirements I needed to meet. So, there was no more utilization gap.”
“The biggest advantages of Cast for us are its ability to scale workloads up and down, pick the most optimal cloud resources for our requirements, and cost-optimize our applications automatically,”
“The solution provided the report I needed for free. Kubecost doesn’t provide data on how much you spend per cluster for free. I finally could see how much I paid for CPUs, memory, and the overall application.”
“If you’re an administrator in a Kubernetes environment and you don’t have this kind of tool, I don’t know how you sleep at night. Thanks to Cast AI, it was the first time that I took a vacation for a month, and nobody asked me to add more nodes to their applications because they’re running a new campaign. I was super happy because of that.”
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“Our clients carry out campaigns, which is the challenge here. We need to ensure the infrastructure meets specific requirements around CPU and memory. We have maybe ten thousand users coming in when a campaign starts, and on other days, the system is not being used at all. We found Cast to be a perfect match for all these cases. Our production, staging, and development environments are handled 100% by Cast.”
“Without Cast, I need to manually define a certain amount of resources: CPUs and memory. Unfortunately, Google Cloud Platform doesn’t provide this customization in brief details. Defining them results in a gap of around 50-60%, which is a waste of resources. When I introduced Cast AI, I noticed that when I created my pods, the newly created infrastructure was based on the exact requirements I needed to meet. So, there was no more utilization gap.”
“We expect to reach savings of around 35% next year due to the fact that we have previously purchased CUDs with Google. They will end next year, and we’re bound to see more savings then.”
“I am super happy with the support, to be honest. I have a private Slack channel with the Cast AI team. After sending a message, I get a fast response. Sometimes the team needs time, but they’re always willing to schedule calls, and I love that. It’s a really lovely way to fix problems.”
“Kubecost has an open-source tool, but the installation and handling of the infrastructure were time-consuming. So, I just started looking and found Cast. The solution provided the report I needed for free. Kubecost doesn’t provide data on how much you spend per cluster for free. I finally could see how much I paid for CPUs, memory, and the overall application.”
“We know that next week we will have a campaign, and that this campaign will involve a certain number of users, even thousands of them. What I did was prescale my infrastructure to have that amount of resources available for the users coming in. But doing this manually took too much of my time.”
“Before Cast, I had to manage nodes myself. Now, it’s not my problem anymore. I can do other things that are more important than workload scheduling and thinking about how many nodes I want, what size they should be, etc. I fully trust Cast to make the best choices here. It’s a massive gain in time for me.”
“Everybody – from a small startup to a large company – should use a product like Cast because it comes with too many benefits to miss.”
“After implementing Cast AI, I finally had the time to focus on developer experience at Voggt or to think about the future of our infrastructure, for example, when we decide to target markets outside of Europe. Or simply the things we could do to have a better infrastructure and deliver a better product for our end users.”
“We got some very good cost improvements because Cast AI did a very good job compacting our Kubernetes cluster and making sure that we’re using only what we need to use. We reduced our cloud costs by 25% using Cast, which is great and very important for us since we’re a startup and costs are very important for investors.”
“Cast AI paid for itself almost by the first day it was activated in production.”
“The support we received was marvelous. I think it was one of the best onboarding experiences and the best support experience I ever got. The Cast team was very reactive, which is especially important when starting a project because we need to move fast and can’t wait days to get our question answered. The team was very nice, and it was a pleasure to work with them during our onboarding.”
“I like to test things fast. When I met one of the Cast co-founders, I instantly trusted him. I trusted Cast, so I thought: Let’s try it, and if it fails, it’s not very important. We’re a startup and can allow it to fail right now. But it didn’t – Cast worked really great from day one.”
“I found Cast AI and immediately thought it looked more approachable. I wasn’t wrong, as the onboarding was very fast with Cast. We were running it in production within one week, while with Spot by NetApp, it was endless testing and support calls.”
“I was using Kubernetes to schedule workloads, but the process wasn’t fast enough. Sometimes, it took almost two minutes to get a new machine in the cluster. This just wasn’t acceptable when we had a lot of traffic coming to the platform. Now with Cast AI, it takes less than 1 minute.”
“An auction must happen in near real time – when you bid on something, you want to do it now and not one second later. It’s very important to have a very low latency between our users and the backends, where possible. So we need to have an infrastructure that is high-performing, efficient, and very fast.”
“By implementing Cast automation, they will be able to use their time wisely and shift the focus from maintaining their Kubernetes clusters to developing new products and features. Cast will not only help them reduce Kubernetes costs, but also give them back their time.”
“Whatever the size of the company or the industry, I strongly recommend Cast AI to every DevOps team. They will see the benefits of Cast immediately.”
“Cast AI also helped our DevOps achieve massive time savings thanks to the automated cluster scheduling.”
“Cast helped us build a full-Spot Kubernetes infrastructure and unlock new savings opportunities. Spot instance interruptions can happen at any time. But since Cast fully and seamlessly handles this, we know there is no impact on our service availability. If a Spot instance is unavailable, Cast will automatically leverage other instance types or fall back to the on-demand instances; no human intervention is needed.”
“The support team is proactive and we always receive the help we need.”
“After testing the platform, I found it to be incredibly intuitive and effective. Within days of connecting my clusters, we experienced substantial savings on our cloud costs – a testament to the remarkable efficiency and reliability of Cast’s solutions.”
“We know that our Kubernetes clusters are continuously optimized, and Cast is picking the cheapest CPU price rate for us automatically. We also don’t need to panic if we see sudden spikes in our traffic or if one of the instance types is no longer available; Cast will handle all of that for us.”
“Cast AI is now in charge of our K8s infrastructure, so our DevOps team can focus on building new applications, improving our internal processes, and testing new features.”
“Whatever the size of the company or the industry, I strongly recommend Cast AI to every DevOps team. They will see the benefits of Cast immediately. By implementing Cast automation, they will be able to use their time wisely and shift the focus from maintaining their Kubernetes clusters to developing new products and features. Cast will not only help them reduce Kubernetes costs, but also give them back their time.”
Peluncuran dan mitra AI
Apa yang telah diluncurkan Cast AI dan dengan siapa ia bekerja sama di bidang AI.
- PeluncuranAI EnablerAI Enabler lets users deploy and run models inside their VPC, autoscale embedding models, and scale based on GenAI metrics.
- PeluncuranAI infrastructureCAST AI offers Kubernetes-native AI infrastructure for running GenAI workloads on spot GPUs and optimizing inference costs.
- PeluncuranPredictive model for KubernetesThe Cast AI Engine is a predictive model for Kubernetes trained on data from clusters and workloads.
Keterampilan yang mereka cari
Paling sering muncul di lowongan terbuka.
Keterampilan paling dicari
- Kubernetes
- Go
- Negotiation
- AI tools
- Prometheus
- TypeScript
- Grafana
- Cloud infrastructure
- Communication
- DevOps
- Salesforce
- CI/CD
Stack teknologi
- Kerangka kerja
- React
- CDN
- jsDelivr
- Amazon CloudFront
- CMS
- WordPress
- HubSpot CMS
- Analitik
- Google Analytics 4
- Google Tag Manager
- Segment
- Pustaka
- jQuery
- Tailwind CSS
- Swiper
- Anime.js
- Pemasaran
- HubSpot
- Keamanan
- CookieYes
Fakta perusahaan
Lowongan per lokasi
Di mana Cast AI merekrut. Pilih kota untuk melihat lowongannya.
Pertanyaan tentang Cast AI
- Apakah Cast AI merekrut?
- Ya. Per 8 Oktober 2026, Cast AI memiliki 31 posisi terbuka di Metaintro. 22 posisi diposting dalam 30 hari terakhir. Paling banyak ada di Sales (9), Developer (8), dan Marketing (3).
- Di mana Cast AI merekrut?
- Cast AI merekrut di Poland, Bulgaria, Hungary, Lithuania, Romania, dan Croatia, dengan lowongan terbuka terbanyak di Poland.
- Apakah Cast AI menawarkan kerja jarak jauh atau hibrida?
- 4% lowongan terbuka bersifat hibrida dan 96% jarak jauh.
- Siapa saja pelanggan Cast AI?
- Cast AI menyebut 4 pelanggan, termasuk Open Assessment Technologies, Voggt, Jisr, dan PlayPlay.
- Keterampilan apa yang dicari Cast AI?
- Lowongan terbukanya paling sering meminta Kubernetes, Go, Negotiation, AI tools, dan Prometheus.