Senior AI Cloud Product Manager

• Define, communicate, and execute a clear cloud infrastructure and AI platform strategy aligned with business objectives and market opportunities.

• Identify opportunities across cloud computing, hosting services, Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Machine Learning operations (MLOps), Model-as-a-Service (MaaS), and AI Agent Platform.

• Own and maintain a strategic technology roadmap for GPU compute (Bare Metal, Virtual Machine, Container), AI Studio, MaaS, and AI Agent Platform.

• Evaluate, propose, and drive adoption of emerging cloud, AI, and MLOps technologies to maintain competitive advantage.

• Lead product vision and execution for AI-native offerings including AI PaaS, AI Studio, Model-as-a-Service, and AI Agent Platform.

• Define products that support the full ML lifecycle — model training, fine-tuning, deployment, inference, and lifecycle management.

• Translate cutting-edge AI capabilities (LLMs, foundation models, AI agents) into scalable, customer-ready services with clear value propositions.

• Gather, document, and prioritize user requirements and product features for cloud, hosting, AI training, inference, and AI agent solutions.

• Engage closely with customers, internal stakeholders, and partners to capture customer needs, market trends, and business priorities.

• Maintain a prioritized product backlog for cloud, hosting, AI Studio, MaaS, and AI Agent features.

• Define and communicate user stories, acceptance criteria, and success metrics for cloud and AI initiatives.

• Define and track AI product KPIs including latency, cost efficiency, model quality, adoption, and customer satisfaction.

• 5–10 years of experience as a Product Manager, with at least 3 years focused on cloud infrastructure, AI platforms, or enterprise technology products

• Strong understanding of cloud computing and hosting services, including IaaS, GPU compute, networking, storage, and containerization (Kubernetes)

• Solid knowledge of AI platforms, AI PaaS, Model-as-a-Service, AI agent frameworks, and the end-to-end ML lifecycle

• Hands-on experience defining products that support model training, deployment, inference, fine-tuning, and lifecycle management

• Familiarity with LLMs, foundation models, and AI service abstractions (APIs, SDKs, orchestration)

• Experience defining and managing product roadmaps, PRDs, and backlogs for complex technical platforms

• Proven ability to work closely with engineering, AI research, infrastructure, and cross-functional teams to deliver scalable solutions

• Strong analytical and problem-solving skills with a data-driven decision-making mindset, including experience defining AI product KPIs (latency, cost, quality, adoption)

• Excellent communication skills with the ability to engage both technical and non-technical stakeholders

• Experience with cloud pricing, capacity planning, or usage-based billing models is a strong plus

Preferred Education Background

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, Data Science, Information Systems, or a related technical field

• Technical education combined with business or product management exposure is a plus

Preferred Hard Skills/Project Experience

• Cloud infrastructure products (GPU cloud, IaaS, virtualization, Kubernetes, container platforms, networking, storage)

• AI Platform / AI PaaS products (end-to-end ML lifecycle, platform abstractions, developer tooling)

• Model services (model hosting, inference APIs, model versioning, scaling, cost optimization, LLM orchestration)

• AI Agents / Agentic systems (LLM orchestration, tool calling, workflows, multi-agent architectures)

• MLOps tooling (model registry, CI/CD for ML, monitoring, evaluation, performance optimization)

• Experience with cloud pricing, capacity planning, or usage-based billing models

• API-driven products, developer platforms, SDKs, or enterprise SaaS solutions

• GPU-based inference and performance optimization is a plus

• A culture that values authenticity and diversity of thoughts and backgrounds;

• An inclusive and respectable environment with open workspaces and exciting start-up spirit;

• Fast-growing company with the chance to network with industrial pioneers and enthusiasts;

• Ability to contribute directly and make an impact on the future of the digital asset industry;

• Involvement in new projects, developing processes/systems;

• Personal accountability, autonomy, fast growth, and learning opportunities;

• Attractive welfare benefits and developmental opportunities such as training and mentoring.