Lead the Solutions Engineering organization at Dust, shaping how AI integrates into enterprise operations.
Posted by employer 3 days ago
First seen on Joblaze 3 days ago
Last verified on the company career page 1 day ago
Skills & Technologies
What you'll build
Must have
Nice to have
AI in the day-to-day
Dust empowers AI Operators to rewire how work gets done.
Not disclosed in this posting: years of experience, visa sponsorship.
Benefits
Joblaze summary
The Global Head of Solutions Engineering at Dust is responsible for leading the technical customer-facing organization, focusing on both pre-sales and post-sales activities to ensure successful enterprise evaluations and deployments. This role requires a strong background in building and scaling technical teams, with expertise in enterprise architecture, AI systems, and customer engagement strategies. Ideal candidates will have a proven track record in transforming customer-facing technical functions and possess the ability to balance hands-on involvement with strategic leadership. Dust's collaborative culture emphasizes in-person teamwork across its global offices, fostering a dynamic envir
Joblaze insights
Quick facts
From the original posting
Dust is hiring a Global Head of Solutions Engineering to build the technical customer-facing organization required for our next stage of growth.
You will lead our global Solutions Engineering function across pre-sales and post-sales. You will own how Dust earns the technical win during complex enterprise evaluations and how we deepen the value, adoption, and stickiness of Dust during and after deployment through advanced use cases and technical solutions.
This is a founding player-coach role. During your first year, you will remain directly involved in our most important customer engagements while significantly scaling the team, and building the repeatable motions that allow the organization to operate without depending on you for every decision.
You will have authority over the organization’s structure, hiring, performance, career paths, technical standards, coverage, resource allocation, and operating model. As a member of Dust’s GTM leadership group, you will work closely with Sales, Customer Success, AI Deployment, Product, and Engineering to connect customer ambition, technical execution, and business value.
The opportunity is larger than building a traditional SE team. You will define how an AI-native Solutions Engineering organization helps customers move from understanding Dust’s potential to making it a critical part of how their companies operate.
Define the global vision, strategy, and operating model for Solutions Engineering at Dust.
Lead the organization across pre-sales and post-sales Solutions Engineering.
Design the team structure, leadership model, roles, career paths, coverage model, operating standards, and performance systems.
Significantly scale the team across Paris, New York, San Francisco and London.
Hire, develop, and manage both Solutions Engineers and future SE leaders.
Establish a high talent bar and build a team that combines technical depth, business judgment, executive presence, and customer empathy.
Create clear decision rights and operating rhythms across regions and functions.
Allocate Solutions Engineering resources based on opportunity complexity, customer impact, strategic importance, and likelihood of success.
Build the systems and leadership capacity required for the function to scale without relying on linear headcount growth.
Define how Dust qualifies, scopes, and executes complex enterprise technical evaluations.
Partner with Sales leadership to improve technical win rate, evaluation conversion, qualified pipeline coverage, and evaluation velocity.
Develop the technical strategy for Dust’s most important enterprise opportunities.
Build a clear understanding of why Dust wins and loses technical evaluations, then turn those insights into improvements across the organization.
Ensure successful evaluations transition into deployment with clear use cases, architecture, dependencies, ownership, and success criteria.
Raise performance across discovery, demonstrations, solution design, pilots, architecture reviews, security validation, and technical handoffs.
Build the post-sales Solutions Engineering motion that helps customers adopt more advanced, valuable, and sticky use cases.
Partner with Customer Success on strategic workshops, complex integrations, new architectures, and technically influenced expansion.
Establish a clear interface with AI Deployment, which owns initial implementation, enablement, production use, and first measurable value.
Turn successful engagements into reusable playbooks, reference architectures, technical assets, and AI-native workflows.
Establish consistent methods for allocating resources, identifying risk, inspecting opportunities, and learning from outcomes.
Reduce dependence on individual heroics while preserving the judgment required for complex enterprise situations.
Turn recurring customer needs into clear input for Product and Engineering.
Strengthen Dust’s technical positioning across enterprise AI, integrations, security, governance, and agent architecture.
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 can deepen 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 the structure needed to scale without creating unnecessary process.
You are a hands-on, low-ego leader who communicates clearly across Sales, Customer Success, AI Deployment, Product, and Engineering.
Advise customers on where AI agents can create meaningful value
Reason about model selection, prompting, context management, tool use, retrieval, evaluations, reliability, latency, and cost.
Explain the capabilities and limitations of modern AI systems clearly to technical teams, business leaders, and executive stakeholders.
Identify integration, security, data governance, and scalability risks.
Reason about APIs, authentication, data connectors, enterprise systems, and cloud architectures.
Design evaluation approaches that connect AI-system performance to customer and business outcomes.
Coach Solutions Engineers through difficult AI, architecture, and customer decisions.
Recognize excellent technical work and hold the organization to a consistently high bar.
Competitive compensation: $275K–$350K OTE
Significant equity package in a Sequoia-backed startup
Relocation support
Health insurance for you and your dependents
New MacBook Pro or Linux machine, monitor, keyboard, etc.
Beautiful office in the heart of NYC
Opportunity to travel to Paris and work with the EU team multiple times a year
Regular team events and offsite
Learn how we think and work.
Our product constitution, a story about our mission
Standard company text repeated across Dust's postings is omitted here.