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Salary: USD 275,000 - 350,000 / annual
Dust is hiring a Global Head of Solutions Engineering to build and lead the technical customer-facing organization for their next phase of growth. You will own the Solutions Engineering function across pre-sales and post-sales, defining how Dust earns technical wins during complex enterprise evaluations and deepens customer value, adoption, and stickiness through advanced use cases and technical solutions.
This is a founding player-coach role. During your first year, you will remain directly involved in the company's most important customer engagements while significantly scaling the team and building repeatable motions that allow the organization to operate independently. You will have full authority over organizational structure, hiring, performance management, career paths, technical standards, coverage, resource allocation, and operating model.
Key responsibilities include:
**Build and Lead the Solutions Engineering Organization**: Define global vision, strategy, and operating model for Solutions Engineering. Design team structure, leadership model, roles, career paths, and coverage across Paris, New York, San Francisco, and London. Hire, develop, and manage Solutions Engineers and future SE leaders. Establish high talent standards combining technical depth, business judgment, executive presence, and customer empathy. Create clear decision rights and operating rhythms across regions and functions.
**Own the Technical Win**: Define how Dust qualifies, scopes, and executes complex enterprise technical evaluations. Partner with Sales leadership to improve technical win rate, evaluation conversion, and pipeline quality. Develop technical strategy for key enterprise opportunities. Build understanding of win/loss patterns and translate insights into organizational improvements. Ensure successful evaluations transition into deployment with clear use cases, architecture, and success criteria.
**Deepen Post-Sales Value**: Build post-sales Solutions Engineering motion for advanced use case adoption. Partner with Customer Success on strategic workshops, complex integrations, and expansion. Establish clear interface with AI Deployment team.
**Make the Function Repeatable**: Turn successful engagements into reusable playbooks, reference architectures, and technical assets. Establish consistent methods for resource allocation, risk identification, and outcome learning. Reduce dependence on individual heroics while preserving judgment for complex situations.
**Raise Technical Bar**: Turn recurring customer needs into Product and Engineering input. Strengthen Dust's technical positioning across enterprise AI, integrations, security, governance, and agent architecture.
Dust is an AI-native platform empowering AI Operators at fast-moving companies to rewire how work gets done. The company has 70%+ weekly active users, serves customers like Datadog, 1Password, Cursor, Clay, Vanta, and Persona, and is backed by Sequoia. The team includes optimists from Stripe, OpenAI, and Stanford who focus on users, ship fast, and aim to 5x growth by end of 2026.
The role requires hands-on leadership with strong communication across Sales, Customer Success, AI Deployment, Product, and Engineering. You will combine technical credibility in enterprise architecture, integrations, security, governance, and AI systems with clear business judgment.
**Requirements**: You have built, scaled, or significantly transformed a Solutions Engineering, Solutions Architecture, Customer Engineering, Technical Account Management, or comparable customer-facing technical function. You have recruited, retained, and developed exceptional customer-facing technical talent across multiple regions, segments, or customer motions. You have owned measurable GTM outcomes and personally helped win complex enterprise opportunities. You understand both pre-sales technical execution and how post-sales Solutions Engineering deepens adoption, value, and expansion. You combine strong technical credibility across enterprise architecture, integrations, security, governance, and AI systems with clear business judgment. You can remain close to strategic customers while building an organization that does not depend on you for every decision. You introduce structure needed to scale without creating unnecessary process. You are a hands-on, low-ego leader who communicates clearly across functions. You can advise customers on where AI agents create meaningful value, reason about model selection, prompting, context management, tool use, retrieval, evaluations, reliability, latency, and cost. You can explain capabilities and limitations of modern AI systems to technical teams, business leaders, and executives. You can identify integration, security, data governance, and scalability risks. You can reason about APIs, authentication, data connectors, enterprise systems, and cloud architectures. You can design evaluation approaches connecting AI-system performance to customer and business outcomes.
