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
The Problem: Current observability tools provide visibility into logs, metrics, and traces, but "stop short of action," leaving engineers to manually interpret data and resolve issues under time pressure.
The Solution: APA bridges the gap between insight and action by introducing agent-like intelligence that proactively identifies issues, takes informed action, and minimizes downtime. It integrates with OpenTelemetry stacks and leverages Kubernetes as its foundational platform.
It builds on real-time observability data from Cast AI products and handles the follow-up work that engineers normally perform manually, for example:
Updating manifests or Dockerfiles when vulnerabilities are detected
Syncing workload rightsizing recommendations into deployment manifests
Proposing indexes or caching strategies for inefficient database queries
Adjusting node templates to improve cluster efficiency
All actions are executed through runbooks - predefined automation workflows that create pull requests, apply configuration updates, or roll back if needed. APA's goal is to fully automate these improvements, reducing repetitive manual work.
The ambition: Rather than being a collection of point solutions, APA is envisioned as a platform where "the whole exceeds the sum of its parts," creating exponential value through intelligent, context-aware automation. Every vertical solution CAST AI develops will become a tool in APA's arsenal, empowering it to take decisive action across the entire software stack.
Requirements:Required:
Minimum of 3-5 years of experience as a Product Manager building B2B SaaS products
Experience in public cloud offerings and Kubernetes - you should understand the DevOps/Platform Engineering workflow
Strong engineering and hands-on mentality; ability to engage deeply with technical concepts, including AI agents, automation workflows, and observability
Proven track record of taking products from 0-to-1 or early stage to product-market fit
Excellent writing skills - you must be able to communicate product features through formats like PR/FAQ or narrative documents that describe feature vision and customer experience
Customer focus and hands-on experience gathering user feedback; strong spoken English required
Familiarity with and willingness to work according to modern product management practices
Self-starter mentality with ability to operate in ambiguous, fast-moving environments
Data-driven approach to decision making with experience in establishing and using product metrics
Education: Information Technology, Computer Science, or similar field
Strongly Preferred:
Experience with AI/ML products or agentic systems
Experience in leading technical products that primarily target engineering user persona
Kubernetes certification (CKA, CKAD) or willingness to complete within first 6 months
Experience working in product-led growth (PLG) environments
Previous experience in early-stage or high-growth startups
Own and drive the development of APA, taking it from early access through product-market fit to general availability
Work directly with beta customers to validate runbook value, gather feedback, and iterate rapidly
Define and execute the product roadmap for new runbooks based on customer pain points and market opportunities
Collaborate with Engineering, UX, Database Optimizer, AI Enabler, and other product teams to deliver high-quality, integrated experiences
Conduct user research interviews and demos to deeply understand customer needs and validate solutions
Drive go-to-market activities, including customer case studies, sales enablement, and early access programs
Work across organizational boundaries to ensure APA integrates seamlessly with existing Cast AI products
Define and track product metrics to measure adoption, engagement, and value delivery
Lead process improvements in the Product Management team and across the wider organization
Champion the voice of the customer in all product decisions and technical discussions
- Competitive salary (€8,000 - €10,400 gross, 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.
- Annual hackathon to spark new ideas and strengthen team bonds.
- 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 Recruiter
- Hiring Manager interview
- 1-2 additional interviews based on the role
- 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.
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