Summary
What you’ll impact
Our company is seeking a Senior Product Manager, AI Cloud Services to lead the definition and launch of its next‑generation AI cloud platform. This 0→1 role involves discovering customer needs, shaping product strategy, and bringing new cloud services to market across engineering, design, commercial, and customer teams.
Responsibilities
What you'll do
- Define the product vision, strategy, and roadmap for Emerald’s Cloud Services platform, shaping how customers access, manage, and optimize AI compute.
- Conduct customer discovery and market research to identify emerging AI infrastructure needs and translate insights into differentiated offerings.
- Define product requirements for AI cloud services, including compute provisioning, management, APIs, developer workflows, and platform capabilities.
- Partner closely with engineering to deliver scalable products while balancing customer needs, technical complexity, and business priorities.
- Work with Sales, Business Development, and Marketing to define packaging, pricing, go-to-market strategy, and drive customer adoption.
- Lead products from initial concept through launch, iteration, and commercialization.
- Bring clarity to ambiguous problems and build alignment across customers, engineering, and business teams.
Requirements
What you’ll bring
- 5+ years of product management experience building cloud infrastructure, developer platforms, or enterprise software.
- Experience launching and scaling customer-facing software products from concept through commercialization.
- Exceptional customer empathy with a strong product discovery mindset.
- Excellent product intuition and ability to identify market opportunities.
- Strong analytical thinking and data-driven decision making.
- Outstanding written and verbal communication skills.
- Experience defining product strategy and prioritizing roadmaps in ambiguous environments.
- Ability to independently lead complex cross-functional initiatives.
- Comfortable operating in a fast-paced, early-stage startup.
- Experience building AI infrastructure products.
- Familiarity with NVIDIA GPUs, Kubernetes, Slurm, or distributed AI training.
- Experience with cloud provisioning, identity, networking, storage, or infrastructure automation.
- Experience working with AI startups, enterprise ML teams, or cloud infrastructure providers.