Global Head of AI Deployment & Partner Delivery (US)
Dust · New York
About this role
## Global Head of AI Deployment & Partner Delivery (US) ### About Dust Dust is building an AI-native way for teams to work with AI agents—backed by enterprise-grade governance, flexible model choice, and a collaborative interface for humans and agents. Dust is used by teams at fast-moving companies (e.g., Datadog, 1Password, Cursor, Clay, Vanta, Persona) and is backed by Sequoia. The company is in a high-growth phase and aims to x5 growth by the end of 2026. ### Summary Dust is hiring a **Head of AI Deployment & Partner Delivery** to make high-impact deployments **repeatable at scale**. This is a **player-coach leadership role**: you’ll lead and grow Dust’s global AI Deployment team, personally drive the most complex deployments, and build the methods, standards, and partner delivery capacity so more customers succeed in 2027 and beyond. You’ll partner closely with **Sales, Customer Success, Solutions Engineering, Partnerships, Product, and Engineering** to connect customer goals to how deployments are planned, delivered, and measured. --- ## What You’ll Do ### 1) Lead and Grow the Global AI Deployment Team - Lead Dust’s existing global AI Deployment team and set direction, priorities, and standards. - Hire and develop deployment leaders and practitioners as demand grows. - Shape roles, career paths, and coverage across regions, segments, and deployment types. - Coach the team through complex customer situations and maintain a consistently high bar. - Set operating rhythms, capacity planning, and reporting to scale. ### 2) Define How Dust Deployments Are Delivered - Build a single deployment method (discovery → handoff) that Dust and partners can follow to the same standard. - Define which deployments Dust leads vs. which partners can deliver well, and how work transitions between the two. - Set entry/exit criteria and go-live readiness checks; track delivery health (e.g., time to first value, go-live quality, customer satisfaction). - Run regular delivery reviews, identify at-risk engagements early, and convene the right Dust/partner teams quickly. - Convert lessons learned into reusable playbooks, templates, and reference architectures; feed recurring friction into Product/Engineering. ### 3) Lead AI Transformation with Strategic Customers - Personally lead complex, high-priority, and first-of-their-kind deployments (scoping → lasting adoption), bringing in Solutions Engineering, Product, and Engineering when needed. - Help customer leaders define what AI transformation means (map current workflows; identify where agents create the most value). - Align executives, IT, security, and business teams on goals, use cases, and success measures—baseline before launch and measure impact after. - Design change programs: executive sponsorship, communications, role-based enablement, and adoption milestones. - Develop AI operators/champions inside customer teams; help customers update governance and ownership so agents become part of how teams operate. - Track adoption post-launch, intervene when teams aren’t changing how they work, and hand off to Customer Success with clarity on next steps. ### 4) Build a High-Quality Partner Delivery Network - Work with Partnerships to assess partner delivery capability, technical depth, and customer readiness. - Start with a small, carefully selected group of partner practitioners; scale capacity as quality is proven. - Co-create onboarding, training, certification, and train-the-trainer programs.
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