GTM Engineer at Dust building automated outbound prospecting systems using AI agents and SaaS integrations. Role combines technical automation with revenue impact, designing workflows in Dust, Clay, CommonRoom, and HubSpot to fuel pipeline growth.
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.
We're hiring a GTM Engineer to scale our automated outbound prospecting systems. This role sits at the intersection of engineering and revenue generation. You’ll combine technical creativity with commercial impact to define what GTM engineering looks like at an AI-first company.
You’ll work directly with RevOps and Sales to build automated workflows, integrations, and AI-powered systems that fuel pipeline growth in the US market. And yes, you’ll be using Dust to build Dust’s GTM engine.
This is a unique opportunity to shape an emerging discipline at a company helping define the future of work.
Build Automated GTM Systems
Design and implement end-to-end outbound workflows using our GTM stack (Dust, CommonRoom, Clay, Lemlist, HubSpot)
Identify high-intent prospects, enrich data, generate personalized outreach, and route qualified leads
Build scalable systems that continuously improve prospecting efficiency
Help define what world-class GTM engineering looks like as the discipline evolves
Enable Sales Impact
Automate repetitive GTM workflows to increase team productivity
Develop playbooks and train Sales teams on automation tools
Help Sales focus on high-value conversations while reaching significantly more prospects
Pipeline Optimization & Experimentation
Own outbound campaigns end-to-end with clear pipeline generation targets
Track performance metrics and optimize based on data
Design and run rapid A/B experiments to improve messaging, targeting, and workflow efficiency
Scale successful experiments into repeatable playbooks
2-5 years of experience in an operations or engineering-focused role
Technical fluency with SaaS tools, APIs, webhooks, automation platforms, and basic scripting
Strong interest in AI and its role in transforming GTM strategies
Business-oriented mindset with an understanding of sales processes and commercial outcomes
Data-driven approach to experimentation and optimization
Scrappy, resourceful problem solver comfortable working in fast-moving environments
Nice to have:
Familiarity with tools in our GTM stack (Dust, Clay, CommonRoom, Lemlist, Default, HubSpot)
Experience in early-stage startups or high-growth environments
Programming experience in Python or JavaScript
You should still consider applying, even if you don’t strictly meet all the requirements above, as long as you have the desire and determination to put your experience in the service of our users.
Competitive compensation: $135K - $200K OTE
Significant equity package at a Sequoia-backed startup
Health benefits for you and your dependents
New MacBook Pro or Linux machine, monitor, keyboard, etc.
Opportunity to travel to the EU multiple times a year
Regular team events and off-sites
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