Senior Solutions Architect - ACE

Aviatrix · USA ·

AI Application Agent

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Job Description
<div><div> </div> <div><br></div></div><p><strong>WHO WE ARE: </strong></p><div> <p>Aviatrix® is pioneering the Cloud Native Security Fabric — the architecture the Containment Era requires. The Cloud Native Security Fabric governs every workload communication path across every cloud, every VPC, every Kubernetes cluster, and every serverless function, from a single policy plane. One rule. Universal propagation. Enforced at the workload, not at a chokepoint. Trusted by more than 500 of the world's leading enterprises. For more information, visit <a href="http://aviatrix.ai" target="_blank" rel="nofollow ugc noopener">aviatrix.ai</a>. </p> <p><strong>About the role: </strong></p> </div><p>We are seeking a Senior Solutions Architect to architect and evolve the customer enablement motion within our Customer Training and Development team. This is a strategic technical role: you will engage pre- and post-sale with enterprise accounts to scope enablement as part of larger deals, partner with Professional Services, Technical Advisors, and Engagement Managers to design customer-specific upskilling paths (including critical upgrade cohorts such as 7.1→8.2+), and use AI to deliver just-in-time curriculum modifications tailored to each customer’s technical environment. You will own curriculum evolution against field signal, not simply teach to a fixed catalog, and serve as a credible technical peer to enterprise architects and CISOs scoping ACE engagements.</p><p><strong><u>Position Responsibilities:</u></strong></p><ul> <li><strong>Technical Delivery &amp; Engagement:</strong> Lead high-stakes ACE workshops and customer-specific enablement sessions, using dynamic ‘Chalk Talk’ and whiteboarding techniques to visualize complex packet flows and multi-cloud architectures. Establish technical credibility with enterprise architects, network leaders, and security stakeholders in the room.</li> <li><strong>Enablement Architecture:</strong> Architect learning solutions against real cust