Senior Product Marketing Manager (Kubernetes Optimization) - Careers @ Cast AI Skip to content Platform Infrastructure Optimization Kubernetes Workload Optimization Standard Cluster Optimization Karpenter Cluster Optimization Database Optimization Infrastructure Observation Kubernetes Cost Monitoring GPU Optimization GPU Sharing GPU Workload Scaling Policies GPU Cost Visibility Cross-cloud GPU Access Custom GPU Edge Location Enterprise AI Coding Token Optimization Enterprise AI Inference Enterprise Agentic Coding Where do you run Kubernetes? AWS GCP Azure Oracle Cloud Application Performance Automation Official APA® Platform How it works Integrations Environments Customers Customers Cybersecurity DevOps E-Commerce Financial Services Industries Gaming & Entertainment Pharmaceutical SaaS All Case Studies Industries Automotive Software & IT AI & ML Setups Transform your cloud-native operations and maximize Kubernetes cost savings Validate Cast AI Get answers Learn about our advanced features Book a Demo Pricing Resources Get Started Documentation Supported Environments Integrations Spot Instance Availability Map Learn Blog Automation Academy Reports Webinars Join the community APA Hero Program Captain Program Slack Community KubeAuto Day Company CAST AI
About Us Newsroom Events Let’s Work Together Careers Partner Program Referral Program Media Brand Assets Contact us Book a demo Sign in Get started Back to Careers Senior Product Marketing Manager (Kubernetes Optimization) European Union; United Kingdom Apply for this role Why Cast AI? Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production. The old way doesn’t work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation. Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS. Global team, diverse perspectives We’re headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead. Unicorn momentum In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we’re just getting started. Join us as we build the future of autonomous infrastructure.
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the role Kubernetes optimization is Cast AI’s core platform and our main competitive battleground . As that surface keeps growing, across the Node Autoscaler, Karpenter Enterprise Suite, and the Workload Autoscaler, we need one person to own the full commercial story. The core platform is growing fast , faster than our commercial story has kept pace with. That’s the opportunity: you’ll build the unified narrative this portfolio is ready for, set the launch discipline that keeps it consistent as new features ship, and give sales messaging they can actually reuse instead of rebuilding it deal by deal. This is a highly technical and strategic role . You’ll act as the voice of the product in the market and the voice of the customer internally, which means translating the same product differently for platform engineers, DevOps and SRE leaders, FinOps teams, VPs of Engineering, and CTOs. That requires real fluency in how software runs, built through marketing technical products, not necessarily through an engineering background. We operate automation-first and market-obsessed, so you’re expected to treat customer and market signals as the input behind every decision, and to build AI-assisted workflows that make this function faster and more consistent over time. You’ll report to the Director of Product Marketing, who sets priorities and goals with you, and you’ll have real support from Product, Content, Demand Gen, Customer Success, and Design. What success looks like in year one Messaging is consistently adopted across launches and by the sales team, not rebuilt deal by deal. Launches land stronger, with measurable product adoption or pipeline impact tied to them. Competitive win rates improve, and the field actually uses the competitive materials you build. Sales has real confidence in the product narrative, not just access to a deck. Customer proof points are quantified, not anecdotal. A repeatable customer and win/loss feedback loop exists and demonstrably shapes Product and GTM decisions.
Requirements: 5+ years in product marketing, with real experience in cloud infrastructure, Kubernetes, DevOps, developer tools, FinOps, observability, databases, or a similarly technical B2B market. Technical fluency. You can talk to engineers and technical audiences without sounding shallow. A track record of turning complex technical products into clear, differentiated messaging for both practitioners and executives. Excellent writing, backed by work samples such as positioning, launch content, sales narratives, or technical thought leadership. Experience leading launches and influencing adoption, pipeline, or competitive outcomes, not just producing launch collateral. Experience leading customer, market, or win/loss research that actually changed a product or go-to-market decision. Strong cross-functional work with Product, Engineering, Sales, Customer Success, and Growth. Comfortable operating without a mature playbook. This function is still being built, and you’ll be defining a process as much as executing against one. Fluent English, written and spoken. What would make you stand out: Owned positioning or GTM for an infrastructure, DevOps, or platform engineering product. Background in AI infrastructure, data platforms, or developer tools. Used customer and deal evidence to shape product strategy and GTM. Evidence of using AI to make your own PMM work faster, more consistent, more reusable, or easier to measure
Responsibilities : Own positioning and messaging for the core platform, including narrative input for external moments like webinars, analyst conversations, and industry events, and keep it consistent as new features ship. Build messaging that explains the same product differently for platform engineers, DevOps and SRE leaders, FinOps teams, VPs of Engineering, and CTOs. Run customer research with core platform buyers to ground positioning in what they actually say, not internal assumptions. Translate the technical mechanics behind each core product into a value narrative technical buyers recognize as true the first time they hear it. Manage feature launches end to end, from early positioning through GA, coordinating timing with Product and rollout with Sales. Build go-to-market plans for core platform releases, including market input to pricing and packaging decisions, and drive plans through execution. Own the competitive assets, narrative, and proof points Sales and Customer Success use with customers, backed by win/loss analysis of what’s actually winning and losing deals. Maintain the feedback loop from customer and market signal back into roadmap input. Track competitive dynamics in this category continuously, and act on it by measuring how each launch actually performs and adjusting from there. Build and maintain AI-assisted workflows that make this function faster, more consistent, or easier to measure. What’s in it for you? Competitive salary (depending on the level of experience). Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Equity options. Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development – including access to international conferences and courses that elevate your skills. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with a Recruiter. Interview with the Hiring Manager. Technical cross-functional interview with Product or Engineering. Practical exercise. Sales/GTM interview. Culture Check interview with an executive. *As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. *Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote Cast AI is the leading APA® (Application Performance Automation) platform, enabling customers to cut cloud costs, improve performance, and boost productivity. Facebook GitHub Slack Community LinkedIn X Solutions Kubernetes workload optimization Standard cluster optimization Karpenter cluster optimization Database optimization Kubernetes cost monitoring Enterprise AI coding & inference GPU Sharing GPU Workload Scaling Policies GPU Cost Visibility Cross-cloud GPU Access Custom GPU Edge Location Resources Blog Events Webinars Reports Customer stories Documentation Release notes Kubernetes Glossary Pricing Company
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