Staff Solutions Architect, Enterprise

The shape of it

In the posting’s own words

Scale builds enterprise AI systems deployed into production. As a Staff Solutions Architect, you lead technical execution on the most complex and highest-value enterprise opportunities in your vertical, and you set the technical standard the rest of the team works to.

What it asks for · 9

• Deep engineering background with substantial experience in customer-facing technical roles at enterprise scale: solutions architecture, sales engineering, forward-deployed engineering, or technical consulting. Hands-on proficiency in Python or equivalent language.
• Track record owning the technical outcome on complex, multi-stakeholder deals with Fortune 500 or equivalent enterprises.
• Strong systems thinking across cloud, data, and AI/ML architecture, with production experience in Generative AI and LLM systems, including agentic systems and their reliability characteristics.
• Demonstrated ability to define evaluation methodology for problems without established metrics, and to negotiate quality bars that survive customer validation and regulatory review.
• Experience operating as a senior technical advisor to executive stakeholders, with the presence to disagree with an executive and retain credibility.
• Evidence of technical work adopted beyond your own engagements: reference architectures, methodologies, processes, or tooling used by others.
• Experience mentoring technical individual contributors and raising the standard of a team.
• Clear technical communication and problem-solving when requirements are unknown, including stating what is not yet known and how it would be determined.
• Deep domain expertise in financial services, healthcare/life sciences, or consumer verticals.

Also a plus

• Recognized externally in your domain: conference speaking, published technical writing, industry forums, or customer advisory participation.
• Experience with domain compliance requirements: model risk management and fair lending (FSI), HIPAA, clinical safety and validated systems (HCLS), or high-volume quality and unit-economics measurement (Consumer).
• Background in forward-deployed engineering or shipping production ML systems.
• Experience creating large-scale evaluation datasets alongside domain experts.
• Experience building or scaling a solutions architecture practice, playbook, or vertical from an early stage.

Tools and skills named

Words the posting leans on

• technical25×
• solutions12×
• architecture7×
• engineering7×
• experience7×
• executive6×
• standard6×
• systems6×
• vertical6×
• complex5×
• evaluation5×
• lead5×
• product5×
• accounts4×
• build4×
• deals4×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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