Scale AI Solutions Engineer at Scale AI leading technical execution for enterprise deals from discovery through post-sale support. Owns technical discovery, evaluation, and prototype development.
Responsibilities
Scale builds enterprise AI systems deployed into production. As a Solutions Architect, you lead technical execution for enterprise deals in your vertical from initial discovery through deal close, and remain involved post-sale to support account growth.
You own an assigned set of enterprise accounts. You conduct technical discovery, evaluate technical feasibility, build solution prototypes, and serve as the main technical point of contact for customer engineering and leadership teams.
You work alongside three primary partners: the Account Executive (commercial owner), the Project Manager (delivery owner), and the Tech Lead (engineering lead for implementation).
What you will own
Technical discovery and qualification. Lead technical discovery and complete the Technical Qualification Checklist, evaluating feasibility, data readiness, integration requirements, security/compliance, evaluation readiness, and stakeholder alignment. Provide clear go/no-go recommendations for prospective deals.
Evaluation and success criteria. Define performance metrics and evaluation criteria before proposal stage, including quality dimensions, baselines, evaluation datasets, and subject-matter expert access requirements.
Customer workshops. Lead executive technical workshops for target use cases. Prepare pre-read materials and build working prototypes or live demos to validate proposed technical architectures.
Statement of Work (SOW) input. Supply the technical input package for SOW creation (architectural approach, prototype findings, risks, dependencies, and assumptions) and review draft SOWs for technical accuracy.
Post-sale account engagement. Maintain long-term technical engagement with signed accounts, identify expansion opportunities for new use cases, and share delivery feedback with GTM teams.
Vertical technical assets. Develop reference architectures, demo environments, discovery templates, and evaluation frameworks for your assigned industry vertical.
What we are looking for
Engineering background with customer-facing experience in solutions architecture, sales engineering, forward-deployed engineering, or technical consulting. Hands-on proficiency in Python or equivalent language.
Qualification
Experience developing with PythonExperience in enterprise SaaS
Required
Strong engineering background with client-facing experience
Experience developing with Python, Java, or other web development languages
Experience in enterprise SaaS, cloud tech, finance, fintech or similar industries
Presentation skills with technical credibility
Effective communication across organizations
Preferred
Experience with domain compliance requirements: model risk management and fair lending (FSI), HIPAA and clinical safety (HCLS), or high-volume quality measurement (Consumer).
Background in forward-deployed engineering or shipping production ML systems.
