Solutions Engineer

Work is being rewritten, and the people holding the pen are the ones who actually run it.

We call them AI operators: the employees inside companies who build, deploy, and run AI agents for their teams, without waiting for someone to hand them a tool. Dust is the platform they choose to rewire how their company works.

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, 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.

As a Solutions Engineer at Dust, you will act as the technical bridge between our sales team and prospective customers, demonstrating how our AI operating system transforms and adds value to their workflows. Your primary focus will be partnering with customers to showcase our solution through technical demonstrations, use case scoping and supporting technical evaluations. You will work closely with our Sales, Customer Success, and Product & Engineering teams to ensure successful customer engagements.

• Product-First: Unlike others focused on building foundation models, we're laser-focused on creating delightful product experiences with existing LLMs.

• Small, High-Impact Team: Join a team of alumni from Stripe, Square, OpenAI, and other top tech companies. We're intentionally keeping our team small and mighty – every individual has massive scope and impact.

• Transparency & Collaboration: Our repository is open source, and we leverage serendipity between team members. We believe the best ideas emerge when the team shares information and insights openly.

• Proactive Problem-Solving: If you see something broken, fix it—without waiting for permission. We don't wait for solutions - we create them.

• Ship to Learn: We move fast and learn from real user feedback.

• Intellectual Humility: We value strong convictions balanced with open-mindedness. Team members confidently advocate for their ideas while remaining receptive to new perspectives and evidence that might change their minds. If new data emerges, we adapt quickly.
  

• Partner with the Sales team to articulate Dust’s value proposition to our prospects and customers and set them up for success

• Provide compelling product demonstrations that showcase Dust's capabilities to both technical and business stakeholders

• Help customers identify high-value use cases that align with Dust's capabilities and their specific business needs

• Create and configure custom LLM agents in Dust to demonstrate practical applications

• Own the technical evaluation end-to-end from customized demos to pilots, helping prospects by onboarding them onto the platform and driving pilot use-cases to completion

• Represent the voice of the customer with Product & Engineering teams to ensure insights and feedback are being implemented into product strategy

• Develop and maintain deep expertise in Dust's API capabilities and prompt engineering best practices

• Educate customers on how to maximize value from generative AI within their workflows
  

• Meaningful experience in a combination of technical and customer-facing roles

• Proven track record of helping customers unlock value from sophisticated software products

• Experience conducting effective technical demonstrations and translating complex concepts to diverse audiences

• Excellent communication and presentation skills with the ability to engage technical and business stakeholders

• Strong technical aptitude with understanding of API concepts and generative AI prompt engineering principles

• Passionate about educating customers of various backgrounds on new technologies

• Ability to speak to both the technical and business value of a solution

• Experience collaborating with cross-functional teams in fast-paced environments

Ideal, But Not Required:

• Experience with AI/ML technologies, particularly generative AI and LLMs

• Background in productivity tools, knowledge management, or workflow automation

• Coding experience to understand API implementations and create custom demos

• Competitive compensation based on experience

• We offer substantial support for relocation, including a stipend up to €10k, finding an apartment in Paris, and supporting you with all residence and work permit-related procedures

• Significant equity package in a Sequoia-backed startup

• Health insurance for you and your dependents

• New MacBook Pro or Linux machine, monitor, keyboard, etc.

• Regular team events and offsites

We're prioritizing building our team with an in-person culture at our offices in Paris and San Francisco, because we value the magic that happens when talented people work closely together.

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