Lead and grow the global AI Deployment team

• Lead Dust’s existing global AI Deployment team and set its direction, priorities, and standards.
• Hire and develop deployment leaders and practitioners as customer demand grows.
• Shape roles, career paths, and coverage across regions, customer segments, and deployment types.
• Coach the team through complex customer situations and hold a consistently high bar for the work.
• Set up the operating rhythms, capacity planning, and reporting the function needs to scale.

Define how Dust deployments are delivered

• Build one deployment method, from discovery through handoff, that Dust and partner teams can both follow to the same standard.
• Define which deployments Dust should lead, which a partner can deliver well, and how work moves between the two.
• Set clear entry and exit criteria and go-live readiness checks, and track delivery health: time to first value, go-live quality, and customer satisfaction.
• Run regular delivery reviews, spot at-risk engagements early, and bring the right Dust and partner people together quickly when a deployment is blocked.
• Turn lessons from each engagement into reusable playbooks, templates, and reference architectures, and recurring friction into clear input for Product and Engineering.

Lead AI transformation with strategic customers

• Personally lead complex, high-priority, and first-of-their-kind deployments, from scoping to lasting adoption, bringing in Solutions Engineering, Product, and Engineering when complexity or risk calls for it.
• Help customer leaders define what AI transformation means for their organization: map how teams work today and identify the workflows where agents can create the most value.
• Align executives, IT, security, and business teams on goals, use cases, and success measures, with a baseline before launch and measured impact after.
• Design change programs for each deployment: executive sponsorship, communication plans, role-based enablement, and clear adoption milestones.
• Develop AI operators and champions inside customer teams, and help customers update ways of working, governance, and ownership so agents become part of how teams operate.
• Track adoption after launch, act quickly when teams aren’t changing how they work, and hand off to Customer Success with a clear picture of what comes next.

Build a high-quality partner delivery network

• Work with Partnerships to assess partners’ delivery capability, technical depth, and customer readiness.
• Start with a small, carefully selected group of partner practitioners and grow capacity as quality is proven.
• Co-create onboarding, training, certification, and train-the-trainer programs so partners can develop their own Dust experts.
• Co-deliver early partner engagements, then help partners progress toward delivering independently, leading adoption, not just implementation.
• Ensure customers experience Dust and its partners as one aligned team, with clear responsibilities on every engagement.

• You have at least 6 years of experience leading and developing customer-facing deployment or delivery teams, ideally across multiple regions or customer segments and through periods of fast change.
• You have led complex enterprise deployments or transformation programs and delivered measurable customer outcomes.
• You have built or significantly improved a deployment methodology, professional services model, or delivery function, adding the structure needed to scale without unnecessary process.
• You have led organizational change alongside technology rollouts, and built champion networks or adoption plans that changed how teams work after the project ended.

You don’t need to be a machine-learning engineer. Beyond that, we care more about evidence that you have built high-performing delivery systems than about a perfect sequence of titles.

• You understand how systems integrators, consultancies, and implementation partners staff, deliver, and grow a practice, and you have built enablement or certification programs that created lasting capability in teams you didn’t manage.
• You have turned around engagements at risk from scope, staffing, technical complexity, or stakeholder misalignment, and you know when to standardize, when to adapt, and when to reset.
• You are credible with customer executives, partner leaders, and technical practitioners, and you communicate clearly with all of them.
• You are a hands-on, low-ego leader with a builder’s instinct: you would rather solve the problem than hand off a recommendation.
• You are comfortable traveling to customers and partners when it matters most.

AI and technical credibility

• Advise customers on where AI agents can create meaningful value and where they can’t yet, and explain why to technical teams, business leaders, and executives.
• Understand how agents work in practice: prompting, context, tool use, retrieval, evaluations, reliability, and cost.
• Challenge a deployment plan’s assumptions about integrations, data connectors, authentication, permissions, security, and production readiness, and discuss the trade-offs with engineers.
• Design evaluation approaches that connect AI performance to customer and business outcomes.

Location

We're prioritizing building our team with an in-person culture at our offices in Paris, London, San Francisco, and New York because we value the magic that happens when talented people work closely together.

We have an office-first culture. Some of the best things about building at Dust are the energy, the fast decisions, and the unexpected conversations that unlock a hard problem, which happen because we are in the same room. Being together is not a formality, it is how we do our best work, and it is something we actively protect.

That said, we hire people with strong judgement and we extend that trust to how they manage their time. When working from home makes more sense for what you need to get done that day, we trust you to make that call.

Why Dust

The models are powerful enough. What's missing is the product layer where AI meets how companies actually work. That's what we're building: the infrastructure that lets any team turn scattered knowledge and tools into coordinated execution with agents they build, own, and run themselves.

We use Dust ourselves every day. We get to shape how humans and agents collaborate while solving our own problems with the product we ship. That loop is rare, and it's why we move fast.

If you're excited about defining a new category and want to join a determined team of optimists who focus on users, ship fast, and don't take themselves too seriously, we'd love to talk.

Even if you don't check every box in our requirements, we encourage you to apply. We value diverse perspectives and backgrounds, and we're more interested in your potential and passion than a perfect match to our checklist.

Learn how we think and work.

• Our product constitution, a story about our mission
• Your Next Co-Worker Isn’t Human , Stanislas Polu , VivaTech 2026. A conversation about AI agents taking on larger parts of work and how teams collaborate with them.
• Dust: Gabriel Hubert on Enterprise AI , Gabriel Hubert , Nasdaq, published May 7, 2026. On Dust’s approach to enterprise AI and building the company in Europe.