As a Senior Solutions Engineer at vCluster, you aren't just giving product demos; you are the technical architect of our enterprise customers' success. Sitting at the high-stakes intersection of Sales and Engineering, you will be a key contributor to our market dominance by leading the "Technical Win" for our most complex, multi-stakeholder deals as we define the Kubernetes virtualization category.

Your Role and Impact

Complex Opportunity Leadership: Own the technical strategy for large-scale enterprise engagements. You will partner with Account Executives to navigate highly regulated industries, developing tailored narratives that solve deep-seated compliance, security, and operational concerns.

Business Value Engineering: Move beyond features to build formal Business Value Assessments (BVAs). You will connect vCluster’s unique capabilities to quantifiable outcomes—linking infrastructure consolidation to actual cost savings, risk reduction, and developer velocity.

AI Literacy & Augmentation: Naturally integrate AI-native workflows to automate discovery documentation, brainstorm complex multi-tenant architecture diagrams, and accelerate GTM delivery. You will use LLMs to analyze customer requirements and extract high-value technical insights while maintaining a "human-in-the-loop" approach to ensure architectural accuracy.

Mentorship & Process Contribution: Act as a force multiplier for the SE organization. You will coach Associate and Intermediate SEs, identify gaps in our qualification frameworks (e.g., MEDDPICC), and design the PoV templates that scale our effectiveness.

The Voice of the Customer: Represent field observations directly to Product and Engineering. You will influence the product roadmap by translating enterprise customer pain into high-fidelity technical requirements.

This Role is a Fit for You If

Proven Experience: You have at least 6 years of experience in a pre-sales or solutions engineering role, with a track record of positioning complex infrastructure or platform solutions to enterprise-level buyers.

Kubernetes Mastery: You have at least 3 years of hands-on experience within the Kubernetes ecosystem. You understand the nuances of control planes, namespaces, and cluster API, and you can explain the trade-offs between legacy multi-tenancy and virtualization.

Cognitive Flexibility: You are an open-minded professional—willing to abandon legacy "spray-and-pray" demo tactics in favor of data-driven, highly targeted consultative selling.

Strategic Thinking: You don't just follow a process; you anticipate market trends and identify complex entry points within the Fortune 2000.

Bonus Points For

Technical Credibility: A CKA or CKAD certification and active participation in the CNCF community or open-source ecosystem.

Regulated Industry Expertise: Deep experience navigating the technical hurdles of Financial Services, Healthcare, or Public Sector environments.

Modern Growth Mindset: You thrive in environments that reject "manual" sales methods and prefer a modern stack where you can solve the revenue puzzle through automation, AI-driven discovery, and technical excellence.

About vCluster Labs

We're the #1 platform for AI infrastructure, trusted by the world's fastest-growing AI cloud builders. We're a venture-backed startup that's raised over $28M from top-tier investors including Khosla Ventures (first investor in OpenAI, GitLab, Stripe, and DoorDash), and we're in a hyper-growth phase looking for motivated people to join our team. Our headquarters are in San Francisco (Salesforce Tower), but our team is distributed around the globe with a remote-first culture.

We give AI Cloud providers and AI factories a hyperscaler-like experience on their own GPU infrastructure. Our platform runs the full stack an operator needs, from bare metal provisioning and node lifecycle management up through managed Kubernetes, Slurm, Ray, and inference clusters, so they can turn raw GPUs into cluster products they can sell in days instead of spending 12+ months building it themselves. Today we power over 100,000 GPUs and 1 million CPUs across 50+ AI clouds and Fortune 500 companies, backed by a team of 40+ infrastructure engineers who build alongside our customers rather than just shipping them software.