Work is being rewritten, and the people holding the pen are the ones who actually run it.
Dust is the multiplayer AI platform for human-agent collaboration. It gives companies a shared workspace where teams can build, deploy, and manage AI agents connected to their company knowledge, tools, and workflows. 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 like Datadog, 1Password, Cursor, Clay, Vanta and Persona, and aim to x5 our growth by the end of 2026.
Dust is backed by Sequoia 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.
Support at Dust is not a cost center. It is one of the most important product surfaces we own.
As a Senior AI Support Engineer, you will help define what world-class support looks like in an AI-native company. You will not just resolve tickets. You will own the systems, agents, workflows, and feedback loops that make support better, faster, and more scalable over time.
This is a senior individual contributor role for someone who has already operated close to support strategy, technical escalation, user experience, and automation. You should be excited by the idea of taking recurring customer pain and turning it into durable systems: better agents, better documentation, better internal tooling, sharper product feedback, and fewer repeat issues.
The best person for this role is not a traditional support leader who wants to manage a queue from a distance. It is someone with strong technical instincts, a deep user mindset, and a track record of building support systems that change how a team operates.
You might be a great fit if you have built an AI-powered support function, owned support tooling at scale, worked deeply with LLMs or automation, or carried a support strategy from problem discovery through implementation and measurement.
You will design, build, and continuously improve the AI-powered systems that help Dust support customers with speed and quality. This includes agents for ticket classification, auto-acknowledgement, response drafting, internal routing, proactive incident detection, knowledge retrieval, and escalation support.
You will identify categories of recurring issues and engineer them out of the support queue. Sometimes that means building a better Dust agent. Sometimes it means improving documentation, creating an internal tool, tightening a workflow, writing a script, or escalating product feedback upstream with enough context for engineering to act.
You will be expected to measure whether the systems you build actually improve the user experience. Seniority here means not just shipping tooling, but knowing what good looks like, instrumenting it, and iterating until the impact is visible.
You will still be close to the work. You will investigate complex customer issues across logs, code, internal tooling, product behavior, and agent outputs. You will provide clear, accurate answers to customers, including when the underlying issue is ambiguous or technically complex.
You will handle escalated cases with precision and judgment, communicating clearly with both technical and non-technical users. You should be comfortable translating between customer language, product behavior, engineering detail, and business impact.
When AI-generated responses are incomplete, inconsistent, or wrong, you will debug the system behind them. You will improve prompts, knowledge sources, workflows, routing, tooling, and escalation paths so that the same failure mode does not repeat.
You will help define how Dust should run support as we scale. That means thinking beyond the queue and owning the full loop: what customers experience, what support sees, what agents can handle, what engineering needs to fix, and what product should learn.
You will translate repeated customer pain into high-quality product signal. You will build strong working relationships with engineers and product teams so escalations are high-context, actionable, and efficient.
You will also help raise the bar for how the support function operates: what we measure, how we prioritize, how we review quality, how we onboard junior team members, and how we decide what should be automated versus handled by a human.
Every candidate and employee’s success at Dust is measured against the same three dimensions: Aptitude, Attitude, and Agency.
You have strong technical depth. You are comfortable with APIs, web applications, logs, scripts, and internal tools. You can navigate a codebase, reason through product behavior, and troubleshoot systems without being stopped by a stack trace.
You have genuine AI fluency at builder level. You have built agents, automations, workflows, or internal tools using AI systems such as Dust, Cursor, Claude Code, n8n, GPT-4, Claude, Mistral, Gemini, or similar platforms. You are not just good at prompting. You understand how to turn AI into operational leverage.
You have experience operating at the strategy layer of support, not only at the ticket layer. You have owned or helped shape support systems, support tooling, escalation workflows, deflection strategy, knowledge management, or AI support operations.
You can balance technical accuracy with user experience. You care about whether the customer understood the answer, whether the product pain was addressed, and whether the issue will happen again.
You are able to communicate bidirectionally: clearly enough for customers, technically enough for engineers, and strategically enough for leadership.
You combine resilience with empathy. This is a front-line role, and customer frustration is often direct and unfiltered. You do not take it personally, but you do take it seriously.
You are proactive rather than reactive. You do not wait for a perfect problem statement from the customer. You investigate, infer, clarify, and anticipate what they may need next.
You have strong prioritization judgment. You know what needs an immediate human response, what can be automated, what should be escalated, and what should become product feedback.
You are comfortable setting boundaries. You do not say yes to everything, and you can explain tradeoffs clearly in a way that builds trust rather than eroding it.
You care about the craft of support. You see support as a product experience, not a back-office function.
You turn patterns into systems. When you see the same issue twice, you start asking whether it should exist at all.
You go deep before escalating. You investigate as far as you reasonably can, so that when you involve engineering or product, they receive a clear problem statement, relevant evidence, and a useful recommendation.
You build without waiting for permission. If you see a gap in the support system, you are excited to prototype, test, and ship a better version.
You continuously improve your own workflows. You treat your time, your tools, and your operating system as things worth debugging.
You extract product opportunities from customer interactions. You do not let support signal disappear into a solved ticket. You close the loop.
You may have:
Built or led an AI-powered support function
Designed support agents, internal copilots, escalation workflows, or deflection systems
Owned technical support tooling, support operations, or automation at a fast-growing software company
Worked as a senior support engineer, technical support engineer, developer support engineer, support ops engineer, solutions engineer, or implementation engineer
Built a support product, internal platform, AI startup, or automation-heavy support system
Operated in a high-volume environment where quality, speed, and judgment all mattered
We care more about the depth and relevance of your experience than the exact number of years. That said, we expect this role to be a fit for someone who has already spent several years close to technical support, support engineering, AI tooling, or support systems ownership.
This is not a traditional customer support role focused only on ticket resolution.
It is not a people-management role where you are far away from the technical work.
It is not a pure operations role where you optimize process without building.
It is not a role for someone who is curious about AI but has not yet built with it.
The person we are looking for should be excited to own the messy middle between customers, AI agents, internal tooling, engineering, and product.
Competitive compensation
Significant equity package in a Sequoia-backed startup
Substantial relocation support, up to 10k€, including help finding an apartment in Paris and support with the visa process
Health insurance for you and your dependents
New MacBook Pro or Linux machine, monitor, keyboard, and equipment
Beautiful office in the heart of Paris
Opportunity to travel to the US multiple times a year
Regular team events and offsites
We can go higher for exceptional profiles.
We're prioritizing building our team with an in-person culture at our offices in Paris, San Francisco, and New York because we value the magic that happens when talented people work closely together.
We have an office-first culture. Some of the best things about building at Dust are the energy, the fast decisions, and the unexpected conversations that unlock a hard problem, which happen because we are in the same room. Being together is not a formality, it is how we do our best work, and it is something we actively protect.
That said, we hire people with strong judgement and we extend that trust to how they manage their time. When working from home makes more sense for what you need to get done that day, we trust you to make that call.
The models are powerful enough. What's missing is the product layer where AI meets how companies actually work. That's what we're building: the infrastructure that lets any team turn scattered knowledge and tools into coordinated execution with agents they build, own, and run themselves.
We use Dust ourselves every day. We get to shape how humans and agents collaborate while solving our own problems with the product we ship. That loop is rare, and it's why we move fast.
If you're excited about defining a new category and want to join a determined team of optimists who focus on users, ship fast, and don't take themselves too seriously, we'd love to talk.
Even if you don't check every box in our requirements, we encourage you to apply. We value diverse perspectives and backgrounds, and we're more interested in your potential and passion than a perfect match to our checklist.
Learn how we think and work.
Our product constitution, a story about our mission
Agents at work - Latent Space, podcast with our cofounder, Stanislas Polu, 2024
LLMs reasoning and agentic capabilities over time - dotAI, podcast with our cofounder, Stanislas Polu, 2024
