Head of Engagement Management

What you’ll do

• Lead and develop a team of Engagement Managers covering Scale's most strategic GenAI lab accounts — hiring, coaching, setting goals, managing performance, and resource planning and allocation across accounts as priorities shift.
• Own account growth strategy for your customer(s), with full accountability for retention, expansion, and commercial development against revenue and growth targets.
• Build and maintain deep, trust-based relationships with frontier AI lab researchers and operations leads, serving as a thought partner across the project lifecycle from ideation to execution.
• Identify and develop new demand generation opportunities in partnership with GTM, and coordinate and track GTM activities across teams at Scale.
• Partner across GTM, ML, Finance, and Delivery Operations to build sustainable, well-resourced account coverage plans and resolve cross-functional tradeoffs. Hold internal teams accountable to customer quality and throughput expectations.
• Set the standard for how your team translates sometimes ambiguous research needs into well-defined human-data programs.
• Build the processes and best practices that evolve the Engagement Management function as Scale's GenAI business and customer set grow.

What we’re looking for

• 6+ years in a technical product/program management, customer success, and/or consulting role, including significant customer ownership in B2B environments.
• Demonstrated ownership of account growth — building new relationships and expanding existing accounts against commercial targets.
• 2+ years managing a team, with a track record of hiring, developing, and retaining strong performers.
• A technical foundation (academic or professional exposure to CS, Engineering, Economics, Statistics, or another STEM field) and a deep understanding of the ML training lifecycle.
• Hands-on experience working with data or AI/ML models through engineering, research, a technical product role, or engagement management itself.
• An action-oriented mindset that balances creative problem solving with the scrappiness to ultimately deliver results.

Nice-to-haves

• A graduate degree (PhD, MS) or research experience in a STEM field.
• Experience at a frontier lab or a company developing foundational models, or a technical leadership role at a high-growth AI company.
• Experience scaling a customer-facing or delivery function (process, tooling, or team build-out).