You will define, communicate, and execute a clear cloud infrastructure and AI platform strategy aligned with business objectives and market opportunities. You will own the strategic technology roadmap for GPU compute, AI Studio, MaaS, and AI Agent Platform, and drive adoption of emerging cloud, AI, and MLOps technologies. You will lead product vision and execution for AI-native offerings, translating cutting-edge AI capabilities into scalable, customer-ready services. You will gather and prioritize user requirements, engage with customers and stakeholders, maintain a prioritized product backlog, define user stories and acceptance criteria, and track AI product KPIs including latency, cost efficiency, model quality, adoption, and customer satisfaction.
Responsibilities
- 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, IaaS, PaaS, MLOps, 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
Requirements
- 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
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, Data Science, Information Systems, or a related technical field
Benefits
- Attractive welfare benefits and developmental opportunities such as training and mentoring