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.

About the role

As a Product Manager at Cast AI, you’ll drive our cloud-native platform forward by gathering user insights, shaping roadmaps, and leading cross-functional teams to deliver impactful, Kubernetes-powered products.

We are currently looking for Product Managers in the following product areas:

Storage Optimization
Reporting
OMNI
Workload Autoscaler

This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.

Requirements

Proven experience owning B2B software products in a cloud-native environment with strong Kubernetes domain knowledge - you understand node lifecycle, autoscaling, and cloud infrastructure economics, not just the PM layer on top of them.
Kubernetes certification (CKA preferred) - you either already hold it or will complete it within your first 6 months.
Demonstrated use of AI tools - LLMs, coding assistants, or agentic workflows - to accelerate product work. You don't need to ship code, but you should already be using AI to reduce cycle time on research, documentation, and decision-making.
Hands-on experience defining and tracking product metrics in B2B SaaS contexts, with the ability to move from raw data to actionable insight.
Excellent writing skills - you can communicate complex technical capabilities through formats like PR/FAQ that make the value clear to both technical and business audiences.
Direct enterprise customer experience - comfortable running discovery interviews and translating ambiguous customer feedback into crisp product requirements.
Familiarity with modern product management practices and a bias toward outcome-driven, evidence-based decision making.
Education: Computer Science, Information Technology, or equivalent practical experience in a technical domain.

Responsibilities

Own a product area end-to-end - from discovery through delivery and adoption - working directly with enterprise customers, SEs, TAMs, and engineering to identify problems worth solving and ship solutions that matter.
Drive customer and market discovery through direct user engagement, Proof of Value cycles, competitive analysis, and close collaboration with the GTM team.
Use AI tools and LLMs actively in your daily workflow - for discovery synthesis, spec drafting, competitive research, customer interview summarization, and pattern recognition across data.
Define and track product metrics that reflect real customer outcomes, using tools like PostHog and control-plane usage data to inform prioritization and validate decisions.
Write clear, structured product narratives - PR/FAQs, one-pagers, feature briefs - that align engineering, design, and stakeholders around a shared understanding of what we're building and why.