Skip to content
ScribeScribe

AI Solutions Engineer

AI Solutions Engineer owns technical aspects of enterprise deals for Scribe Optimize, leading demos, POCs, and ROI narratives while bridging sales, customer success, and product teams. Requires 5+ years pre/post-sales experience and strong AI fluency.

About the job

Why This Role Matters

We're building something new. As Scribe's first-ever AI Solutions Engineer, you'll be an expert in Scribe's most complex products, bridging the gap between closing deals and delivering outcomes. You'll partner with AE and CSM teams, earn trust of F1000 executives, design solutions, and lead Proof of Concepts for Scribe Optimize.

About the Role

As an AI Solutions Engineer at Scribe, you will:

  • Own the technical layer of enterprise deals, partnering with Account Executives from discovery through close — running tailored Optimize demos, leading POC planning sessions, and designing proof of concepts.
  • Execute Scribe Optimize POCs, ensuring prospects see immediate value.
  • Build and communicate ROI narratives grounded in real workflow data.
  • Serve as a bridge between GTM and Product, acting as the primary voice of the customer for Optimize.
  • Develop repeatable playbooks for pre-sales technical motions, POC execution, and post-sale onboarding.
  • Address technical and security questions during enterprise deal cycles.
  • Maintain deep technical knowledge across Scribe’s Workflow AI capabilities.

What Makes You a Great Fit

You'll thrive if:

  • 5+ years in Solutions Engineering, Solutions Architecture, Technical Account Management, or similar at high growth SaaS.
  • Strong AI fluency: LLMs, architecture, prompt design, model behavior.
  • Comfortable working with AI/ML Engineering teams.
  • Understand Scribe's Workflow AI technical framework.
  • Understand enterprise workflows (Salesforce, ServiceNow, SAP).
  • Build trust fast, data-driven, ROI-obsessed, collaborative.

Bonus points:

  • Process mining (Celonis, UiPath), AI product deployment, founding roles, consulting, enterprise AI security.

Compensation

$180,000 – $225,000 OTE + equity (80% base / 20% variable)

Skills

AI, LLMs, Prompt Design, Workflow Ai, Salesforce, Servicenow, SAP, Process Mining, Celonis, Uipath, Poc, ROI Analysis

Tracebit

Tracebit

New York, NY

Founding Sales Engineer
$180k+/yrRemote3+ YOESales Engineering

The founding Sales Engineer will lead technical discovery, demos, Proof-of-Values, and customer guidance while partnering with sales, product, and engineering. The role requires 3–5 years of customer-facing technical experience, ideally in cybersecurity or developer tooling, plus cloud infrastructure or DevOps knowledge.

Envoy

Envoy

New York, NY

Pre Sales Solutions Engineer
$178k+/yrOn-siteSales Engineering

Leads technical pre-sales for EMEA accounts through demos, discovery, proof-of-concept scoping, and security reviews. The role requires expertise in identity systems, web infrastructure, APIs, EU data protection, and communicating with senior technical stakeholders.

Hex

Hex

San Francisco, CA
Partner Solutions Engineer
$177k+/yrRemote5+ YOESales Engineering

Build and scale Hex’s technical partner enablement program through curricula, demos, onboarding, training, and strategic deal support. The role requires 5+ years in solutions engineering or architecture, strong SQL and Python skills, modern data-stack experience, and excellent presentation abilities.

Hex

Hex

San Francisco, CA
Sales Engineer, Commercial Mid-Market
$175k+/yrRemote3+ YOESales Engineering

Partners with sales to guide mid-market prospects through technical evaluations of Hex's collaborative data platform, owning demos, POCs, and security reviews. Requires 3+ years in sales engineering and familiarity with Python, SQL, and data workflows.

Artie

Artie

San Francisco, CA

Sales/Solutions Engineer
$175k+/yrOn-site5+ YOESales Engineering

Own technical discovery, proof-of-value engagements, and solution design for enterprise data platform customers. The role requires 5+ years in solutions or sales engineering, strong data architecture expertise, and familiarity with databases, cloud warehouses, cloud infrastructure, and Kafka.