Director of Product, Ecosystem
Nebius
| Company | Nebius |
| Category | Product |
| Location | Remote - United States |
| Remote | Remote |
| Employment | Not stated |
| Level | Director |
| Salary | Not stated by the employer |
| Posted | 28 May 2026 |
| Last verified | 12 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role
Nebius builds the infrastructure serious AI teams run on — GPU clusters, inference runtimes, agent development environments, data pipelines — all of it purpose-built for the most demanding AI workloads. What we are now building is the ecosystem function that ensures the best AI companies choose to build on us, integrate with us, and stay.
The Director of Product, Ecosystem owns the external view of one or more Nebius platform layers. You will map who matters, engage the targets that count, prototype what a partnership actually looks like on our stack, and translate everything you learn into new platform capabilities and product decisions.
You’re welcome to work remotely in the United States .
Your responsibilities will include:
Strategy
Own the ecosystem map for your platform layer — who matters, what they build, where the gaps are relative to our platform strategy
Define which companies to engage and why — a prioritized target list with a thesis behind every name
Translate external landscape signals into concrete build vs. buy vs. partner recommendations for product and exec leadership
Sourcing
Lead outbound engagement with founders, operators, and investors across your ecosystem domain
Build peer-level relationships in the AI startup founders — the kind where people call you before they announce anything
Identit y partnership, integration, and M&A targets before they are obvious to the market
Solutioning
Prototype integrations between partner products and the Nebius stack — fast, hands-on, and technically sound
Scope partner architectures against our platform — how does this product actually work on our stack, where does it snap together, where does it break
Define the technical narrative and reference architecture for each partnership
Produce working proof-of-concepts that serve as the starting point for product creation — not a requirements doc, a working thing
Internal
Work with ISV partners, SI teams, and field teams to scale solution adoption and drive revenue once a solution is ready
This entire motion — inception, experimentation, prototyping — serves as a pipeline for new platform capabilities and product development
Bring outside-in frontier signal into the company and help leadership make the right choices on where to invest
Participate in platform planning as the external voice of the ecosystem
Platform focus areas
Depending on your background and mutual fit, you will own one or more of the following:
Agentic — agent frameworks, memory systems, tool integration, orchestration, guardrails
Managed Inference — inference runtimes, model routing, optimization tooling, serving infrastructure
IaaS / Managed Infrastructure — cloud-native integrations, GPU orchestration, sovereign cloud, enterprise infrastructure
Data — vector databases, retrieval systems, data pipelines, labeling infrastru