D

Dust

Enterprise AI agent platform

Global Head of AI Support Engineering

Customer SupportConfirmed live in the last 24 hours
Full-timeÎle-de-France, France

About the Job

Requirements

  • You've defined or significantly shaped a support engineering function before, including building the operating model, setting standards, hiring into the team, or rebuilding a process from scratch.
  • You are comfortable reading code, analyzing logs, navigating codebases, and troubleshooting distributed systems.
  • You have a track record of building custom agents, automations, or workflows using AI tools such as Dust, Cursor, Claude Code, or n8n, rather than only prompting.
  • You can prioritize what to solve immediately, automate, escalate, and delegate, for yourself and the team.
  • You've coached and developed engineers, set expectations, given direct feedback, and raised team performance.
  • You can translate technical concepts for non-technical audiences and communicate fluently with engineers.
  • You believe strong Support Engineering teams build systems that prevent recurring issues.
  • You instinctively automate repetitive work and hold your team to the same standard.
  • You can absorb customer frustration without taking it personally while caring about user experience.
  • You lead by example and are willing to handle difficult work directly.
  • You thrive in ambiguity and enjoy building systems from scratch where processes are undefined.
  • You share knowledge and care about the broader team's success.
  • You take ownership by defining work and identifying functional gaps without waiting for direction.
  • You focus on eliminating categories of work rather than only resolving tickets faster, and hold yourself and the team accountable to that distinction.
  • You turn recurring issues into scalable systems, automations, workflows, or documentation that prevent future occurrences.
  • You investigate issues thoroughly before escalating, provide engineering teams with thoughtful, high-context information, and coach the team to do the same.

Responsibilities

  • Set the technical direction for the support stack, deciding what to automate, in what order, and to what standard.
  • Design, ship, and maintain AI agents and automation workflows that reduce manual support work, including ticket classification, acknowledgment automation, response drafting, incident detection, and proactive user outreach.
  • Identify recurring issue categories and engineer them out through automation, documentation, prompt iteration, or product feedback.
  • Build and maintain tooling, including MCP integrations, Dust agents, and internal scripts, to increase team capacity without increasing headcount.
  • Define and own the Support as a Product backlog, decide what it contains, coach the team to execute it, and set the quality bar for shipped work.
  • Hire, onboard, and develop support engineers.
  • Set standards for handling complex issues and personally take the hardest tickets.
  • Investigate complex issues across logs, code, and internal tooling to identify root causes and provide clear customer answers.
  • Handle escalated cases with precise, accessible communication for technical and non-technical audiences.
  • Analyze agent-generated responses for inconsistencies and iterate on prompts, documentation, and tooling to minimize human intervention.
  • Represent Support at the engineering and product level by synthesizing and prioritizing customer signals and advocating for improvements with sufficient context.
  • Build working relationships with engineers and customer-facing teams to enable efficient, high-context escalations.
  • Own the end-to-end feedback loop and close gaps across engineering, product, and documentation when agents fail because of missing or incorrect information.

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

Recently Posted Jobs

Explore more opportunities at Dust

See more jobs