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Nebius

Runs GPU clouds for AI training and deployment

Director of Product - Ecosystem

Technical Product ManagementConfirmed live in the last 24 hours
Full-time$228k - $285kIn-person

About the Job

Requirements

  • At least 8 years of relevant experience building technical products, with meaningful ownership of AI infrastructure, cloud platforms, or developer tools.
  • A track record of taking products from an ambiguous customer problem to production adoption, with measurable outcomes.
  • Strong technical fluency and the ability to work through architecture and implementation decisions with engineers.
  • Ability to use APIs and SDKs, explore unfamiliar tools, and build working prototypes to test product thinking.
  • Experience designing developer experiences across APIs, integrations, documentation, and operational workflows.
  • Familiarity with how AI applications are built and an informed perspective on the infrastructure needs of increasingly agentic systems.
  • Strong customer discovery skills and sound judgment about which needs can support a repeatable product.
  • Ability to communicate clearly in writing and verbally, including product proposals, technical tradeoffs, and investment recommendations.
  • Comfort setting direction, making decisions, and delivering in a fast-moving environment.
  • Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility as a condition of hire.

Responsibilities

  • Own the product vision, priorities, and roadmap for emerging opportunities in agentic infrastructure.
  • Work directly with developers and enterprise teams to understand their workflows, technical constraints, and unmet needs.
  • Translate customer insights and ecosystem developments into clear product decisions and scoped releases.
  • Partner with engineering and design throughout discovery, development, launch, and iteration.
  • Define success through developer adoption, production usage, customer outcomes, and business impact.
  • Build prototypes, sample applications, and integrations to test ideas and make product decisions concrete.
  • Use Nebius and relevant ecosystem tools firsthand to understand the developer experience and identify gaps.
  • Work through technical tradeoffs with engineering, including performance, reliability, security, and cost.
  • Validate new concepts with customers and turn successful experiments into production offerings.
  • Create reference architectures and examples that make it easier for developers to get started.
  • Build close relationships with founders, technical leaders, and developers shaping how AI applications are built.
  • Evaluate emerging tools and technologies through direct experimentation and customer feedback.
  • Identify where Nebius should build, integrate, or partner to deliver a stronger product experience.
  • Lead the product side of selected partnerships, from initial concept through integration, launch, and adoption.
  • Bring external insights into platform planning and help leadership prioritize investments.
  • Work with developer relations, marketing, sales, and field teams to bring new capabilities to market.
  • Stay close to early users, resolve adoption barriers, and feed production learnings into the roadmap.
  • Develop a repeatable path from customer discovery and experimentation to products with sustained usage.

Desired Qualifications

  • Founded a company or served as an early product or engineering leader at an AI or infrastructure startup.
  • Built products used by developers to create or operate AI applications.
  • Experience with distributed systems, cloud infrastructure, or production AI workloads.
  • Contributed to open-source projects or worked closely with developer communities.
  • Built technical partnerships that led to successful integrations or new product capabilities.

About the Company

Nebius

Runs GPU clouds for AI training and deployment

Nebius runs an AI cloud for developers, researchers, and enterprises that train models and put them into production. Its AI Cloud combines GPU computing, storage, networking, and managed services, while Token Factory runs models through an API so teams do not manage the underlying servers. Customers rent computing and storage at usage rates or reserve capacity, choosing resources that fit short experiments or sustained production workloads. Beyond the cloud, the group owns Avride, which develops autonomous vehicles and delivery robots, and TripleTen, which teaches technical skills for people changing careers. The publicly listed group is headquartered in Amsterdam, Netherlands.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Amsterdam, Netherlands
Founded
1997

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