Solutions Engineer

Domino Data Lab

Solutions Engineer enabling enterprise customers' success by demonstrating Domino's data science capabilities. Collaborating on technical strategies and proof-of-concept deployments for impactful outcomes.

Posted 5/5/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $200,000 - $250,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPython

About the role

Key responsibilities & impact

Lead technical evaluations and demonstrations of the Domino platform for Enterprise customers in a multitude of industry verticals
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 industry-specific 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 prospect accounts

Requirements

What you’ll need

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 Enterprise customers, understanding their procurement processes, compliance constraints, and security environments
Track record of leading successful technical evaluations or pilots that resulted in multimillion-dollar enterprise software deals
Experience working in complex 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, Azure, GCP), and networking concepts
Understanding of the end-to-end AI lifecycle, from experimentation to production.

Benefits

Comp & perks

equity
company bonus or sales commissions/bonuses
401(k) plan
medical, dental, and vision benefits
wellness stipends.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonRdata sciencemachine learningcontainerizationDockerKubernetesAWSAzureGCP

Soft Skills

collaborationsolution architecturecustomer successtechnical evaluationscommunication