Solutions Engineer

About Dust 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. This Role As a Solutions Engineer at Dust, you’ll serve as the technical bridge between Sales and prospective customers, demonstrating how our AI platform transforms the way teams work. You’ll partner closely with prospects to identify high-impact use cases, deliver tailored demonstrations, and guide technical evaluations from initial discovery through successful pilot deployments. This is a highly hands‑on role, where you’ll help customers move beyond concepts and into real, working implementations on Dust. You’ll work cross‑functionally with Sales, Customer Success, and Product & Engineering to ensure every engagement clearly demonstrates business impact and sets customers up for long‑term success. What you’ll do Partner with Sales to drive technical wins Act as a trusted technical counterpart to Account Executives throughout the sales cycle Clearly articulate Dust’s value to both technical and business stakeholders Build credibility and trust with customers by combining strong technical fluency with a consultative, customer‑first approach Help shape the foundation of Dust’s global Pre‑Sales Solutions Engineering organization as one of our first US hires Lead technical discovery and product evaluations Run deep technical discovery to uncover high‑impact use cases aligned with customer workflows and business priorities Design and deliver tailored, high‑impact product demonstrations grounded in real customer problems Own the technical evaluation process end‑to‑end, from discovery and custom demos through hands‑on pilots and technical validation Guide prospects through onboarding and help them deploy meaningful use cases during pilot phases Build solutions that make AI tangible Build lightweight prototypes, agents, workflows, or integrations that demonstrate practical applications of Dust Develop deep expertise in Dust’s platform capabilities, AI workflows, and prompt engineering best practices Help customers move beyond curiosity about AI into real operational impact inside their organizations Translate complex AI concepts into clear, actionable guidance for both technical and non‑technical audiences Influence product and help scale the function Translate customer feedback and technical pain points into actionable insights for Product and Engineering Identify patterns across customer conversations and pilots that help shape product direction and go‑to‑market strategy Help establish best practices, technical playbooks, and repeatable processes as the Solutions Engineering team grows Operate comfortably in ambiguity while helping define what great AI‑native Solutions Engineering looks like at Dust Requirements Every candidate and employee’s success is measured against the same 3 dimensions. Aptitude , Attitude and Agency . Aptitude You have experience in roles that combine deep technical fluency with customer‑facing work, such as Solutions Engineering, Forward Deployed Engineering, or Technical Consulting You’ve successfully supported complex, consultative sales cycles involving multiple stakeholders across technical and business teams You’re comfortable working with APIs, software integrations, and interconnected systems, and can quickly ramp on new technical concepts You have experience building demos, prototypes, workflows, or lightweight technical solutions in pre‑sales or post‑sales environments You can translate complex technical concepts into clear business value and adapt your communication style based on the audience You’ve helped customers adopt and realize value from sophisticated software platforms, especially in technically complex environments You actively explore generative AI workflows, prompt engineering, and emerging AI‑native tooling Attitude You’re deeply curious and excited by rapidly evolving technology, especially AI and how it changes the way teams work You thrive in ambiguity and enjoy operating in fast‑moving, early‑stage environments where processes are still being defined You bring a collaborative, low‑ego approach and work effectively across Sales, Product, Engineering, and Customer Success teams You enjoy solving hard problems and are energized by technical challenges that don’t yet have obvious answers You’re proactive, resourceful, and naturally look for ways to move projects and customer outcomes forward You care deeply about customer experience and approach customer interactions with empathy, credibility, and ownership Agency You take ownership end‑to‑end, from initial technical discovery through pilots, evaluations, and successful customer outcomes You proactively identify gaps, propose solutions, and build what’s needed rather than waiting for perfect requirements or direction You experiment with new approaches, test ideas quickly, and adapt based on customer feedback and evolving product capabilities You’re comfortable operating with limited structure and can drive meaningful outcomes independently in ambiguous situationsYou have a builder mindset and create scalable assets such as demos, templates, integrations, workflows, or technical playbooks that improve the broader team You consistently look for ways to improve technical evaluations, customer adoption, and cross‑functional collaboration Nice to Have Experience working with AI/ML technologies, particularly generative AI and LLM‑based products Background in productivity tools, knowledge management, collaboration platforms, or workflow automation Ability to write code (Python, JavaScript, etc.) to work with APIs, automate workflows, or build demos and prototypes You should still consider applying even if you don’t meet every requirement above. We care deeply about curiosity, ownership, adaptability, and the desire to help customers succeed with transformative technology. Compensation and Benefits Competitive compensation: $135k–$240k OTE We offer substantial support for relocation Significant equity package in a Sequoia‑backed startup Health insurance for you and your dependents New MacBook Pro or Linux machine, monitor, keyboard, etc. Beautiful office in the heart of San Francisco Opportunity to travel to Paris and work closely with the founding team Regular team events and offsite Location 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. 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, 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 #J-18808-Ljbffr