Engagement Management Lead

Scale AI Scale AI · Data AI · New York, NY +1 · Gen AI Operations

This role focuses on managing strategic customer relationships within Scale's Generative AI business, acting as a liaison between customers and internal teams to ensure successful project delivery and identify expansion opportunities. The Engagement Manager will work with customer data leaders and engineering/operations teams, emphasizing the importance of high-quality data for Gen AI models.

What you'd actually do

  1. Own a portfolio of complex, strategic projects with full accountability for delivery, quality, customer sentiment, and commercial outcomes
  2. Build and maintain deep, trust-based relationships with customer researchers and leads, serving as a thought partner throughout the project lifecycle
  3. Navigate difficult customer conversations around pricing, quality, and delivery expectations with confidence and clarity
  4. Identify and develop expansion opportunities through close customer engagement and a strong track record of execution

Skills

Required

  • 5+ years of work experience
  • experience in consulting or as a technical product or program management role
  • proven track record in B2B client-facing roles
  • building and expanding relationships
  • navigating complex customer dynamics
  • technical background (education or professional experience with CS, Engineering, Economics, Statistics, or another STEM field)

Nice to have

  • Graduate degree (PhD, MS) or research experience in a STEM field
  • Experience at a frontier lab or company developing foundational models, or in a technical role at a high-growth AI company
  • Hands-on technical experience working with data or AI/ML models, whether through engineering, research, or a technical product role

What the JD emphasized

  • strong interest in how high-quality data can positively influence Gen AI models
  • track record of earning new work through the quality of their execution and relationships
  • Ability to understand the ML training lifecycle and discuss use cases meaningfully with technical customers