Dust

AI Support Engineer Lead (US)

San Francisco

Sponsorship not specified$240k-$350kDetected 6 days ago

LinuxDatadogLLMsAgentic AICommunicationCollaboration

About the role

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.

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.
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.
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.
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.
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.

Exceptional prioritization: You know what to solve immediately, what to automate, what to escalate, and, critically, what to delegate and to whom.
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.
Resilience-empathy paradox: You can absorb customer frustration without taking it personally while still deeply caring about the user experience.
Exceptional prioritization: You know what to solve immediately, what to automate, and what to escalate.

Agents at work
Latent Space https://www.youtube.com/watch?v=U5wFQOb4eI4, podcast with our cofounder, Stanislas Polu, 2024

Investigate complex issues across logs, code, and internal tooling to identify root causes and provide clear answers to customers.
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.

This listing is sourced directly from Dust's careers page and normalized into a canonical job model.