Dust is a multiplayer AI operating system that enables businesses to deploy, orchestrate, and govern fleets of specialized AI agents connected to company knowledge and tools.
ABOUT DUST Work is being rewritten, and the people holding the pen are the ones who actually run it. With enterprise-grade governance, flexible model choice, and a collaborative interface for humans and agents to work together, Dust empowers AI Operators at the world’s fastest-moving companies to rewire how work gets done. With 70%+ weekly active users, people stick with Dust as much as they do with Slack and Notion. We don't get piloted and shelved. We land once, and spread. We're at an exciting stage of our journey, and growing fast. We're serving great customers https://dust.tt/customers like Datadog, 1Password, Cursor, Clay, Vanta and Persona, and aim to x5 our growth by the end of 2026. Dust is backed by Sequoia https://techcrunch.com/2024/06/27/dust-grabs-another-16-million-for-its-enterprise-ai-assistants-connected-to-internal-data/ with a determined team of optimists (coming from Stripe, OpenAI, and Stanford) who like to focus on users, ship fast, and don't take themselves too seriously while doing so. The Generalist named us among the Future 50 https://www.linkedin.com/posts/dust-tt_were-honored-to-be-recognized-on-the-generalists-activity-7359284343929741313-Rq04. SUMMARY At Dust, we're coining the term AI Operator: someone who rethinks and rebuilds company processes around AI. Not "how can AI help us do this faster?" but "if AI existed from day one, would we even do this the same way?" The AI Support Engineer applies this mindset to Support. You'll split your time between running support (handling complex issues when agents fall short) and building the AI systems that reduce that workload over time. Support at Dust is not a cost center, it's a product. Success is measured by eliminating categories of tickets, not just resolving them. You will define, ship, and continuously iterate on the infrastructure that lets Dust deliver a world-class support experience at scale: AI agents, automation workflows, classification systems, knowledge systems, and tooling built on top of Dust itself. You will dogfood the product harder than almost anyone at the company. We're hiring depending on your experience and technical depth. You'll be an experienced support engineer ready to build systems at scale, we want to hear from you. WHAT YOU'LL DO BUILD THE AI SYSTEMS THAT DO THE WORK - Set the technical direction for the support stack: what gets automated, in what order, and to what standard. You make the calls, not just the builds. - Design, ship, and maintain AI agents and automation workflows that reduce manual support load: think ticket classification, acknowledgment automation, response drafting, incident detection, and proactive user outreach. - Identify recurring categories of issues and engineer them out of existence through automation, documentation, prompt iteration, or product feedback. - Build and maintain tooling (MCP integrations, Dust agents, internal scripts) that increase the team's capacity without increasing headcount. - Define and own the "Support as a Product" backlog. You decide what goes on it, coach the team to execute it, and hold the bar on what shipped means. RUN SUPPORT WHEN THE SYSTEMS FALL SHORT - Hire, onboard, and develop the support engineers around you. You're not just resolving tickets and building systems, you're growing the people who will. - Set the standard for how complex issues get handled at Dust. You take the hardest tickets yourself. The team knows what good looks like because they've watched you do it. - Investigate complex issues across logs, code, and internal tooling to identify root causes and provide clear answers to customers. - Handle escalated cases with precise, accessible communication for both technical and non-technical audiences. - Systematically analyze agent-generated responses for inconsistencies and iterate on prompts, documentation, and tooling until human intervention is minimal. BRIDGE CUSTOMER PAIN TO PRODUCT IMPROVEMENTS - Represent support at the engineering and product level. You synthesize signal, prioritize it, and push it through with enough context that it actually moves things, not just relays it. - Build strong working relationships with engineers and customer-facing teams to ensure efficient, high-context escalations. - Own the feedback loop end-to-end: when agents fail due to missing or incorrect information, close the gap across engineering, product, and documentation. REQUIREMENTS Every candidate and employee's success is measured against the same 3 dimensions: Aptitude, Attitude and Agency. APTITUDE - Function-building experience: You've defined or significantly shaped a support engineering function before: built the operating model, set the standards, hired into the team, or rebuilt a broken process from scratch. - High technical aptitude: comfortable reading code, analyzing logs, navigating codebases, and troubleshooting distributed systems. You're not stopped by a stack trace. - AI fluency at builder level: track record of building custom agents, automations, or workflows using AI tools (Dust, Cursor, Claude Code, n8n, etc.); not just prompting. - Exceptional prioritization: You know what to solve immediately, what to automate, what to escalate, and, critically, what to delegate and to whom. You make these calls for yourself and for the team, fast and without second-guessing. - People development instincts: You've coached and grown engineers before, even informally. You know how to give feedback that sticks and create conditions where people do their best work. - Bidirectional communication: can translate technical concepts to non-technical audiences and speak technical language fluently with engineers. - Interest in or experience with a Build/Run split: Whether you've already operated this way or you're excited to learn this approach, you see support as more than ticket resolution. ATTITUDE - Builder mentality: You instinct