Enablement Lead

Raspberry AI•New York, NY

About The Position

Raspberry AI is hiring its first Enablement Lead to manage AI Implementation Specialists and Solution Engineers, the teams that connect its product with customers. The role will build a unified function with shared operating rhythms and playbooks, clear handoffs from presales through onboarding and adoption, and a hiring plan that scales with the customer base. It is a player-coach position, combining team and program leadership with hands-on involvement in strategic accounts and deals. The Enablement Lead will manage and develop the team, hire and onboard new members, and establish capacity planning, account coverage, and work assignment across presales and post-sales. The role owns the enterprise customer journey from discovery and demos through onboarding, training, go-live, and adoption, while developing enablement materials and training programs for customers. In partnership with Sales leadership and account executives, the Enablement Lead will ensure Solution Engineers support the right deals and that presales commitments align with implementation. The role will use adoption data to identify expansion opportunities and churn risks, bring fashion expertise into customer workflows and demonstrations, relay prioritized customer feedback to Product and Engineering, and measure and improve team performance. The position also requires keeping current with product releases and developments in generative AI.

Requirements

At least 7 years of experience across solutions engineering, implementation, enablement, or customer success.
At least 3 years of experience managing a team.
Experience leading both presales and post-sales teams, or a mixed team with a handoff between the two.
Experience building an onboarding or enablement program from scratch.
Comfort working with enterprise customers, including leading discovery calls and executive demos and helping recover stalled implementations.
Hands-on familiarity with AI and creative tools; uses generative AI in their own work and can explain it to skeptical designers.
Experience setting team metrics, building dashboards, and using data to inform staffing and process decisions.
Strong writing and communication skills and ability to work effectively with Sales, Product, and Engineering.

Nice To Haves

Background in fashion, retail, apparel, or footwear, especially in design, product development, or merchandising.
Experience at a Series A or Series B startup building a function as it scaled.
Familiarity with fashion-team PLM, 3D, or creative tools such as Centric, Browzwear, CLO, or Adobe.
Experience supporting customers in both the US and UK/EU.

Responsibilities

Manage AI Implementation Specialists and Solution Engineers through regular one-on-ones, goal setting, performance management, and career development.
Define role profiles, interview candidates, and onboard new team members.
Establish capacity planning, account coverage, and assignment of work across presales and post-sales.
Design handoffs between Sales, Solution Engineering, Implementation, and Customer Success so customer context is retained.
Own enterprise customer onboarding, including kickoff, workflow mapping, training, and go-live.
Build customer enablement programs, including onboarding playbooks, role-based training, office hours, and certification.
Partner with Sales leadership and account executives to ensure Solution Engineers support appropriate deals across discovery, tailored demos, proofs of concept, and technical evaluations.
Ensure that presales demonstrations and commitments align with implementation delivery.
Use adoption data to identify expansion opportunities and flag churn risks.
Lead Implementation Specialists in demonstrating creative workflows, model outputs, and practical use cases for customer teams.
Turn customer successes into reusable demo assets, case studies, and templates.
Provide Product and Engineering with clear, prioritized customer input.
Define and report team metrics, including time-to-first-value, activation, adoption by team, presales win rate, and training satisfaction.
Keep the team up to date on Raspberry product releases and the generative AI landscape.