Senior AI Cloud Product Manager

What you will be responsible for 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. How you will stand out 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 What you will experience working with us 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. Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, colour, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union. #J-18808-Ljbffr