Solutions Engineer Post-Sales

Job description

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. 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 https://dust.tt/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 https://techcrunch.com/2024/06/27/dust-grabs-another-16-million-for-its-enterprise-ai-assistants-connected-to-internal-data/ 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 https://www.linkedin.com/posts/dust-tt_were-honored-to-be-recognized-on-the-generalists-activity-7359284343929741313-Rq04. TLDR; As a Post-Sales Solutions Engineer at Dust, you will act as the technical partner for our existing customers, ensuring they maximize value from our AI operating system throughout their journey with us. Your primary focus will be driving long-term customer success through value realization, identifying expansion opportunities, and creating high-value, sticky use cases that make Dust indispensable to their operations. You will work closely with our Customer Success and Product & Engineering teams to deepen customer relationships and drive retention. RESPONSIBILITIES - Develop and maintain deep expertise in Dust's product, platform capabilities, and prompt engineering best practices to serve as the internal expert for customer scenarios - Serve as a trusted technical advisor to our Enterprise customers, building deep relationships with both technical and business stakeholders over time - Lead advanced implementation projects, including high-value, high-impact use cases, technical integrations and custom workflows - Lead training & workshop sessions, effectively communicating Dust's value proposition to buyers and evaluators (e.g. security and compliance teams). You must possess strong technical acumen and high emotional intelligence (EQ) to adapt explanations and presentations to the audience, ensuring clarity and engagement. - Partner with Customer Success to drive high-value adoption, retention and expansion among your book of business - Champion customers' needs with Product & Engineering teams, translating usage patterns and feedback into product requirements and roadmap priorities - Be instrumental in building our global Solutions Engineering organization from the ground up as our first post-sales SE hires, with the opportunity to define processes, establish best practices, and lay the groundwork for future team expansion REQUIREMENTS - 4+ years in a combination of technical and customer-facing roles (e.g. software engineering, solutions architect, implementation engineer). - An action-oriented and organized self-starter mindset who isn’t afraid to get scrappy to solve customer issues. - A strong work ethic and commitment to excellence. - A deep interest in understanding customer needs and the desire to become an expert on Dust’s product. - Strong relationship-building skills with ability to establish yourself as a trusted technical advisor - Effective multitasking and prioritization skills under pressure and in ambiguous situations across a wide variety of tasks. - Demonstrated ability to work collaboratively with cross-functional teams to achieve shared goals. - A data-driven mindset that can interpret customer feedback and behavior. - A passion for technology, problem-solving, and a commitment to your customers’ success. - High technical aptitude, with an ability to work directly with engineers as well as business stakeholders. Experience with APIs, web development, and writing scripts to build internal tools is a plus. Familiarity with LLMs like GPT-4, Claude, Mistral or Gemini is highly desirable. LOCATION 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. WHY DUST 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, https://blog.dust.tt/a-first-version-of-our-product-constitution/ a story about our mission - Agents at work - Latent Space https://www.youtube.com/watch?v=U5wFQOb4eI4, podcast with our cofounder, Stanislas Polu, 2024 - LLMs reasoning and agentic capabilities over time https://youtu.be/8d1PtJBnAEM?feature=shared - dotAI, podcast with our cofounder, Stanislas Polu, 2024