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Scribe is a specialized intelligence platform used by 94% of the Fortune 500 to capture how work happens and turn it into a living asset. The company has grown to 90,000+ customers and 7 million users since 2019, is valued at over $1 billion, and is backed by leading investors.
As a Solutions Engineer, you will be a technical expert bridging the gap between closing enterprise deals and delivering transformational outcomes. Working in partnership with Account Executives and Customer Success teams, you'll earn the trust of F1000 executives as a technical authority on Scribe's Workflow AI capabilities, designing groundbreaking solutions and communicating what's possible.
You'll own the technical layer of enterprise deals from discovery through close, running tailored Optimize demos, leading POC planning sessions, and designing proof of concepts tied to measurable customer outcomes. You'll build ROI narratives grounded in actual workflow data, making time saved and costs avoided concrete numbers rather than claims. You'll clear technical and security questions during enterprise cycles, working with the Engineering team to resolve configuration issues and keep procurement moving.
You'll carry the voice of the customer to the Product team with evidence attached, documenting what's working, what isn't, and what customers need next. You'll turn learnings into repeatable pre-sales assets and playbooks so subsequent deals of similar shapes move faster. You'll hold deep working knowledge of Scribe's platform and serve as a technical reference point for the go-to-market team.
You'll be part of a brand new team defining how Scribe wins and delivers on its most strategic product, Scribe Optimize. You'll build the playbook from scratch, work shoulder-to-shoulder with Sales, CS, and Product teams, and leave your fingerprints on how the company scales.
The role is pre-sales focused and stays close to the deal. SF-based candidates work hybrid (3 days/week in office); NYC candidates are fully remote. Travel is up to 30% to meet customers and prospects.
REQUIREMENTS:
- 5+ years in Solutions Engineering, Solutions Architecture, Technical Account Management, or comparable pre-sales technical role at a high-growth SaaS company
- Strong AI fluency: understand how large language models work, speak credibly about LLM architecture, prompt design, model behavior, and AI output quality
- Comfortable working directly with AI/ML Engineering teams, translating customer requirements into technical context and participating in solutioning conversations
- Ability to understand and articulate Scribe's Workflow AI technical framework—how workflow data is captured, processed, and surfaced as insights—and explain it clearly to technical and non-technical audiences
- Understanding of enterprise workflows and operational processes; experience with tools like Salesforce, ServiceNow, and SAP; knowledge of how companies think about process improvement and automation
- Ability to build trust quickly with executive stakeholders and end users; skill in anchoring technical conversations to outcomes that matter to each audience
- Builder mindset energized by ambiguity; excited to define this function rather than step into a pre-made role
- Data-driven and ROI-obsessed; ability to build business cases, validate assumptions, and help customers see real, quantifiable impact
- Collaborative and low-ego; thrives in team environments, partners closely with AEs and CSMs
NICE TO HAVE:
- Experience with process mining, workflow intelligence, or operational analytics tools
- Work inside an AI/ML product team or deployment of AI-powered products in enterprise context
- Founding or first-of-its-kind role at a high-growth SaaS company
- Familiarity with enterprise AI security reviews, model governance frameworks, or responsible AI practices
