[Hiring] Senior Solutions Engineer @vCluster Labs

Role Description

As a Senior Partner Solutions Engineer at vCluster Labs, you aren’t just supporting partner deals; you are building the technical foundation of our partner ecosystem from the ground up. You will be our first dedicated partner-facing pre-sales engineer, turning relationships with NVIDIA, WWT, AMD, and AI Cloud providers like Nebius into validated reference architectures, enabled partner architects, and partner-sourced pipeline.

Your role will include:

• Joint Reference Architectures: Design and validate reference architectures with strategic partners, from NVIDIA blueprints and AMD foundations up through the platform layer: vCluster, vNode, vMetal, and vCluster Platform. Turn one successful deployment into a repeatable, sellable solution with bills of material, deployment guides, demo environments, and benchmarks.
• Partner Enablement: Build and deliver technical enablement for partner architects and sellers, including training dozens of architects at partner Centers of Excellence on the value proposition, cost, and performance story of the vCluster product family.
• Field Enablement: Enable vCluster’s internal field SEs to engage partners effectively, so the partner motion scales beyond one person and the field is never pulled off customers to cover channel work.
• Partner-Led Opportunities: Own technical discovery, demos, and Proofs of Concept for partner-sourced opportunities, always in support of direct field ownership.
• Centers of Excellence: Stand up vCluster presence inside partner Centers of Excellence, such as WWT’s in St. Louis, tied to named customers and qualified pipeline rather than marketing labs.
• Ecosystem Navigation: Build technical credibility across a focused set of 6–8 priority partners, cultivating executive sponsors and technical champions without becoming dependent on a single contact or business unit.

Qualifications

• Deep Kubernetes expertise: You go deep on cluster architecture, Tenant Isolation, and the cloud-native ecosystem, and you can master vCluster, vNode, and vMetal inside and out.
• Partner pre-sales experience: You have worked with partners (OEMs, GSIs, resellers, or cloud providers) in a technical pre-sales capacity and you understand the partner dynamic: co-selling, joint validation, and winning through someone else’s sellers.
• Solutions engineering craft: Years of discovery, whiteboarding, demos, and POCs that actually convert to production, with the qualification discipline to say no to science projects.
• Enablement building: You have created enablement content, workshops, hands-on labs, or certification paths from scratch, and the partners you enabled kept winning after you left the room.
• Executive presence: You can hold the room with a Kubernetes engineer and a CIO in the same meeting, and you move people you don’t manage.

Requirements

• Bonus points for:
• NVIDIA ecosystem experience: DGX, Dynamo, GPU Operator, AI Enterprise, or NVIDIA certifications, plus an understanding of how NVIDIA blueprints and partner validation actually work.
• AI infrastructure depth: GPU infrastructure, storage, and networking for AI factories and GPU clouds (Weka- and VAST-class storage literacy is a plus).
• AI Cloud or GPU-as-a-Service experience: Time building or supporting GPU-as-a-Service or Kubernetes-as-a-Service platforms at AI Cloud providers or service providers.

Benefits

• Competitive Salary: We offer a competitive compensation package, including equity.
• Platinum-Level Insurance: Health, dental, vision, and life Insurance, including plans for you and eligible dependents (benefits vary depending on country).
• Flexible Working Schedule: We won’t have an issue with you needing to adjust your schedule for personal appointments.
• Workplace Flexibility: We’re very flexible about where you work and are happy to adjust the work environment for you.

Company Description

We are a venture-backed tech startup pioneering Kubernetes virtualization for the AI era. Our headquarters are in San Francisco (Salesforce Tower), but our team is distributed globally with a remote-first work culture.

We are the leading platform for operating GPU infrastructure, enabling AI Cloud providers to deliver a hyperscaler-like experience to their customers and AI factories.

We're the company behind vCluster, an open-source technology for virtualizing Kubernetes, with a strong emphasis on community and innovation.