AI Enablement Lead, Headspace Health

• 5+ years of experience in Product Ops, Technical Program Management, Business Operations, or equivalent roles delivering software/AI projects end-to-end
• Strong cross-functional leadership, change management, and stakeholder management; ability to influence without authority across Product/Eng, Legal/Privacy/Security, Procurement, and functional leaders
• Comfort operating in ambiguity and driving crisp decisions, scope, milestones, and delivery plans
• Strong aptitude of AI concepts (LLMs/agents, common tradeoffs, prototype→pilot→scale lifecycle) and ability to translate technical constraints into clear timelines and decision points
• Ability to define success metrics for initiatives and measure outcomes (directly or in partnership with analytics/data teams)
• Excellent written and verbal communication (exec one-pagers, workshops, playbooks, enablement sessions)
• Strong judgment and commitment to member safety, privacy, and Headspace’s mission

Desirable

• This role is for a hands-on AI builder and adoption leader—a curious, product-minded problem solver who moves fast, spots leverage, and turns messy ambiguity into shipped workflows, tools, and outcomes across the company
• As the AI Enablement Lead, you’ll drive company-wide adoption end-to-end: building repeatable intake and prioritization, moving pilots to production, equipping teams with playbooks and training, and helping initiatives clear governance smoothly
• You’ll influence across all teams at Headspace, building the muscle for experimentation and scaled adoption through enablement, evangelization, and hands-on execution
• You’re fearless and constructively contrarian: willing to challenge defaults, run smart experiments, and unblock teams while staying inside responsible AI guardrails. Help build AI agents that give our teams the leverage they need to #make-the-mission-matter
• Own AI intake and prioritization: triage requests, refine problem statements, size value, and maintain a transparent queue
• Lead AI initiatives end-to-end (discovery → pilot → launch), aligning scope, milestones, success metrics, and stakeholders. Own the outcome and drive real impact by building
• Build and run AI enablement (training, office hours, playbooks, and an AI Champions network) to drive adoption and fluency
• Grow awareness and adoption of existing AI tools with functional leaders to expand use cases and impact
• Standardize AI vendor evaluation and guide tools through governance with Product, Legal, Privacy, Security, Procurement
• Champion responsible AI through measurement, training, and org-wide communication
• Deliver lightweight reporting and exec-ready updates on pipeline health, outcomes, and trade-offs
• Unblock high-leverage technical/integration work and identify next-wave AI opportunities to scale adoption and cultural change
• What success looks like (first 90 days):
• A single, working AI intake + prioritization system is live, with clear criteria and a visible queue
• An AI enablement cadence is running (office hours + champions network + basic playbook library)
• At least 1–2 pilots move from idea → UAT/launch with measurable outcomes
• A repeatable vendor evaluation + governance checklist exists (privacy/security/procurement artifacts), reducing cycle time for new tools and pilots