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Dust

Enterprise AI agent platform

Global Head of AI Deployment & Partner Delivery

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeÎle-de-France, France€130k - €160k /yr

About the Job

Requirements

  • 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.
  • Experience leading complex enterprise deployments or transformation programs and delivering measurable customer outcomes.
  • Experience building or significantly improving a deployment methodology, professional services model, or delivery function, adding structure to scale without unnecessary process.
  • Experience leading organizational change alongside technology rollouts and building champion networks or adoption plans that changed how teams work after a project ended.
  • Understanding of how systems integrators, consultancies, and implementation partners staff, deliver, and grow a practice, and experience building enablement or certification programs that created lasting capability in teams not directly managed.
  • Experience turning around engagements at risk from scope, staffing, technical complexity, or stakeholder misalignment, and knowing when to standardize, adapt, or reset.
  • Credibility with customer executives, partner leaders, and technical practitioners, and ability to communicate clearly with all of them.
  • Hands-on, low-ego leadership and a builder’s instinct to solve problems rather than simply hand off recommendations.
  • Comfort traveling to customers and partners when it matters most.
  • Ability to advise customers on where AI agents can create meaningful value and where they cannot yet, and explain why to technical teams, business leaders, and executives.
  • Understanding of how agents work in practice, including prompting, context, tool use, retrieval, evaluations, reliability, and cost.
  • Ability to challenge deployment-plan assumptions about integrations, data connectors, authentication, permissions, security, and production readiness, and discuss trade-offs with engineers.
  • Ability to design evaluation approaches that connect AI performance to customer and business outcomes.

Responsibilities

  • 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 maintain a consistently high bar for the work.
  • Establish operating rhythms, capacity planning, and reporting for the function to scale.
  • Build a deployment method from discovery through handoff that Dust and partner teams can follow to the same standard.
  • Define which deployments Dust should lead, which partners can deliver, and how work moves between them.
  • Set entry and exit criteria and go-live readiness checks, and track delivery health through time to first value, go-live quality, and customer satisfaction.
  • Run regular delivery reviews, identify at-risk engagements early, and bring the appropriate Dust and partner staff together when a deployment is blocked.
  • Turn engagement lessons into reusable playbooks, templates, and reference architectures, and communicate recurring friction as input for Product and Engineering.
  • Personally lead complex, high-priority, and first-of-their-kind deployments from scoping to lasting adoption, involving Solutions Engineering, Product, and Engineering when complexity or risk requires it.
  • Help customer leaders define AI transformation for their organizations by mapping current workflows and identifying where agents can create the most value.
  • Align executives, IT, security, and business teams on goals, use cases, and success measures, establishing a baseline before launch and measuring impact afterward.
  • Design change programs for each deployment, including executive sponsorship, communication plans, role-based enablement, and clear adoption milestones.
  • Develop AI operators and champions within customer teams and help customers update ways of working, governance, and ownership so agents become part of team operations.
  • Track adoption after launch, act when teams are not changing how they work, and hand off to Customer Success with a clear view of next steps.
  • 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 and help partners progress toward independent delivery and leading adoption, not just implementation.
  • Ensure customers experience Dust and its partners as one aligned team, with clear responsibilities on each engagement.

About the Company

Dust

Enterprise AI agent platform

Dust provides a horizontal, open-source platform for building, deploying, and managing custom AI agents that connect to a company’s data and tools. It acts like an AI operating system by integrating with data sources and apps like Slack, Notion, Google Drive, and GitHub, and supports multiple LLM providers with a no/low-code interface, building blocks, and a scripting language to parse outputs. It targets non-technical users to automate tasks and gain insights across departments, focusing on deployment and productization of AI rather than model development. It differentiates itself with model-agnostic compatibility, strong security (SOC 2 Type II, GDPR), and a horizontal B2B SaaS strategy aimed at broad enterprise adoption.

Company size
51-200
Company stage
Series B
Total funding
$62M
Headquarters
Paris, France
Founded
2023

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