AI Support Engineering Lead (US)

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 building for a new kind of AI Operator: people who rethink and rebuild how their teams work 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?” As our AI Support Engineering Lead, you'll own how Support is built and scaled at Dust. This is a deeply hands-on role. You'll take on the hardest customer issues when our agents fall short, but your job isn't simply to resolve them. You'll look for the pattern behind each issue and turn what you learn into better agents, automation, tooling, documentation, and product improvements. Over time, you'll help grow the team and shape how Support Engineering operates as Dust scales. You'll define, ship, and continuously iterate on the systems that make this possible: AI agents, automation workflows, classification systems, knowledge systems, and tooling built on top of Dust itself. You'll dogfood the product harder than almost anyone at the company and set the standard for how the rest of the Support Engineering team does the same. We're looking for someone who wants to lead from the work: technically strong, obsessed with building better systems, and excited to shape both the team and the function as we grow. 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 leadership: You've coached and developed engineers and know how to set expectations, give direct feedback, and raise the performance of the people around you. - Bidirectional communication: can translate technical concepts to non-technical audiences and speak technical language fluently with engineers. - Build/Run mindset: You believe the best Support Engineering teams don't just resolve issues. They build systems