Director of Product, Ecosystem

Posted Yesterday
Be an Early Applicant
Hiring Remotely in United States
Remote
265K-315K Annually
Senior level
Artificial Intelligence • Information Technology • Consulting
The Role
The Director of Product, Ecosystem is responsible for managing partnerships and integrations in the AI space, guiding product strategy and development, and engaging with external companies.
Summary Generated by Built In

Why work at Nebius
Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Where we work
Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

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
  • Identity 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 infrastructure, synthetic data 

We expect you to have: 

  • 8+ years operating across product strategy, business development, and ecosystem or partnership development in AI or infrastructure
  • Deep technical fluency in at least one of our platform layer domains — you understand the architecture, the players, and the dynamics from having been close to the work, not just reading about it
  • Genuine relationships in the AI founders and VCs — people take your call because of who you are, not what company you are calling from
  • Experience as a founder, early operator, or investor in AI or infrastructure — you understand how startups make decisions and what they actually need from a platform partner
  • Comfort going hands-on — you can prototype an integration, scope a partner's architecture, and produce a working proof-of-concept without waiting for an engineer to do it for you
  • Strong written and verbal communication — you can present a partnership thesis to a VP of Product and a Series A founder in the same week and be credible in both rooms
  • Comfortable building without a playbook — you create the process, you do not wait for it 

It will be an added bonus if you have:  

  • Founded or been an early operator at a company building in one of our platform layer domains
  • Operated as an EIR or investing partner at a top-tier AI-focused VC fund
  • Built an ecosystem or platform partnership function from scratch at a high-growth AI or infrastructure company
  • Structured and closed technology partnerships through to LOI or acquisition
  • Familiarity with NVIDIA's software stack, inference tooling, or agent development frameworks 

Key Employee Benefits:

  • Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
  • 401(k) Plan: Up to 4% company match with immediate vesting.
  • Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
  • Remote Work Reimbursement: Up to $85/month for mobile and internet.
  • Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.

Compensation

We offer competitive salaries, ranging from $265k - $315k OTE (On Target Earnings) + Equity based on your experience.

Compensation

We offer competitive compensation packages based on experience.

Compensation Range
$265,000$315,000 USD

What we offer: 

  • Competitive salary and comprehensive benefits package.
  • Opportunities for professional growth within Nebius.
  • Flexible working arrangements.
  • A dynamic and collaborative work environment that values initiative and innovation.

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

Equal Opportunity Statement:

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply, and will be required to provide proof of employment eligibility as a condition of hire.

Skills Required

  • 8+ years in product strategy, business development, or ecosystem development in AI or infrastructure
  • Deep technical fluency in platform layer domains
  • Genuine relationships in AI and VC communities
  • Experience as founder, operator, or investor in AI or infrastructure
  • Ability to prototype integrations and produce proof-of-concept
  • Strong written and verbal communication skills
  • Comfortable creating processes and working without a playbook
Am I A Good Fit?
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The Company
473 Employees

What We Do

Cloud platform specifically designed to train AI models

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