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Solutions Engineer, Public Sector

Company
Domino Data Lab
Location
Remote
Work type
Hybrid · Remote · Remote
Posted
2026-08-07

Job description

What your impact will be

Lead technical evaluations and demonstrations of the Domino platform for customers across the Department of Defense, civilian agencies, federally funded research and development centers (FFRDCs), and major defense contractors.
Design and execute proof-of-concept deployments tailored to each customer’s environment and mission needs, showcasing Domino’s integration with their data science workflows and infrastructure.
Collaborate with account executives to craft solution architectures that meet federal security and compliance standards (e.g., FedRAMP, IL5).
Develop and maintain reusable demonstration environments and technical assets that accelerate future sales cycles.
Drive post-POC adoption readiness by partnering with Customer Success and Solutions Architects to ensure a smooth handoff into deployment.
Success will be evident through higher technical win rates, reduced time to close, and increased adoption within key government accounts.
What we look for in this role

Security Clearance: This position requires an active U.S. Secret Security Clearance (US Citizenship required), with the ability to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) Security Clearance and program access (post start). A U.S. Security Clearance that has been active in the past 24 months is considered active.
Proven success in pre-sales or solutions engineering, ideally supporting enterprise software or AI/ML platforms. This does not necessarily need to be at a software vendor, equivalent solution engineering tasks internally or as a consultant developer could work.
Experience with U.S. public sector customers, especially within federal agencies, defense, or national labs — understanding their procurement processes, compliance constraints, and security environments.
Track record of leading successful technical evaluations or pilots that resulted in multimillion-dollar enterprise or government software deals.
Experience working in complex, highly regulated IT environments, including hybrid or air-gapped systems.
Proficiency in Python, R, and modern data science / machine learning tools.
Familiarity with containerization (Docker, Kubernetes), cloud platforms (AWS GovCloud, Azure Government, GCP), and networking concepts.
Understanding of the end-to-end AI lifecycle, from experimentation to production.
What we value

We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply
We value a growth mindset. High-performing creative individuals who dig into problems and see the opportunities for success
We believe in individuals who seek truth and speak the truth and can be their whole selves at work
We value all of you that believe improving is always possible. At Domino, everything is a work in progress – we can do better at everything
We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company

Skills Required
Active U.S. Secret Security Clearance (US Citizenship required) with ability to obtain Top Secret/TS/SCI and program access
Proven success in pre-sales or solutions engineering supporting enterprise software or AI/ML platforms
Experience with U.S. public sector customers (federal agencies, DoD, national labs, FFRDCs) and procurement/compliance constraints
Track record leading technical evaluations/pilots that resulted in multimillion-dollar enterprise or government software deals
Experience in complex, highly regulated IT environments, including hybrid or air-gapped systems
Proficiency in Python, R, and modern data science / machine learning tools
Familiarity with containerization and orchestration (Docker, Kubernetes), cloud platforms (AWS GovCloud, Azure Government, GCP), and networking concepts
Understanding of end-to-end AI lifecycle from experimentation to production

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