Partnerships Solutions Engineer

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 looking for a Partnerships Solutions Engineer to help build the technical foundation of Dust's partner ecosystem in the US.

You'll work closely with our Partnerships, Sales Engineering, Product, and partner teams to turn relationships into repeatable solutions and customer outcomes. You'll help partners develop AI offerings on Dust, establish the frameworks to deliver them successfully, and build the technical capabilities to bring those solutions to market.

This is a hands-on role for someone who enjoys working at the intersection of AI, technical implementation, and go-to-market strategy.

• Collaborate with consulting and technology partners to develop packaged AI solutions and service offerings built on Dust.

• Translate partner expertise and customer workflows into reusable agent templates, demos, and solution blueprints.

• Help identify compelling use cases that partners can take to market and replicate across customers.

• Create practical implementation playbooks covering discovery, solution design, deployment, and customer onboarding.

• Build reusable technical assets and reference architectures that help partners deliver Dust-powered solutions more efficiently.

• Work with partner delivery teams to establish the skills and processes needed to implement solutions independently.

• Lead technical workshops, solution design sessions, demos, and proofs of concept with strategic partners and customers.

• Help partners understand Dust's capabilities, integrations, APIs, and MCP ecosystem.

• Equip partners with the knowledge and materials to confidently position, demonstrate, and deliver Dust.

• Partner with Sales Engineering, Product, and Engineering to address technical blockers and improve partner solutions.

• Bring feedback from partner implementations into product and integration priorities.

• Work with Partnerships to support joint opportunities and identify where repeatable solutions can drive pipeline and adoption.

• Experience in Solutions Engineering, Technical Consulting, Forward Deployed Engineering, or a similar customer-facing technical role.

• Hands-on experience building AI applications, agents, automations, or enterprise software integrations.

• Strong understanding of MCPs, APIs, technical architecture, and connecting business systems and workflows.

• Ability to translate customer problems into practical technical solutions and repeatable implementation approaches.

• Strong communication skills and the ability to work effectively with technical teams, consultants, and business stakeholders.

• A builder mindset: comfortable with ambiguity, able to prioritize, and motivated to create repeatable processes from scratch.

• Experience working with consulting partners, systems integrators, or technology alliances.

• Familiarity with MCP, LLMs, and modern AI tooling.

• Experience developing partner solutions, implementation playbooks, or packaged consulting offerings.

• Partners can confidently demonstrate and implement Dust-powered solutions.

• Partners have repeatable offerings and delivery frameworks they can use across multiple customers.

• Successful implementations translate into reusable assets, faster delivery, and less reliance on Dust's internal teams.

• Partner-led opportunities and deployments increase as the ecosystem matures.

We're prioritizing building our team with an in-person culture at our offices in Paris, London, 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.

• Our product constitution, a story about our mission

• Your Next Co-Worker Isn’t Human, Stanislas Polu, VivaTech 2026. A conversation about AI agents taking on larger parts of work and how teams collaborate with them.

• Dust: Gabriel Hubert on Enterprise AI, Gabriel Hubert, Nasdaq, published May 7, 2026. On Dust’s approach to enterprise AI and building the company in Europe.