• Lead the SpecOps OpEx & AI enablement: Own the embedded operational excellence initiatives for SpecOps, with a focus on AI‑enabled tools, workflows, and mechanisms that improve quality, efficiency, and customer trust across Concierge, EES, ResoOps, and Premium Inbound. • Turn pain points into AI solutions: Build an intake and prioritization model that translates negative sentiment and escalation patterns into a ranked backlog of AI / automation / tooling and product opportunities, sequencing work to maximize customer and business impact. • Design and scale a unified signal fabric: Standardize a single, real‑time customer‑ and contact‑impact signal fabric across proactive and reactive experiences, quality, fraud/risk, and operational health—reducing detection‑to‑action from hours to minutes. • Operationalize AI‑powered workflows for specialists: Stand up and continuously refine agent‑facing AI solutions (e.g., research helpers, summarizers, decisioning and routing engines, opportunity modeling, incident analysis chains) that reduce handle time, improve accuracy, and eliminate low‑value work. • Establish specialized operating models and routing: Define and scale resolution operating models that route enriched, prioritized tasks to the right teams, favor back‑office and systemic fixes first, and only trigger authenticated, high‑trust outreach when needed to reduce friction and recontact. • Define the KPI stack and instrumentation: Own the KPI framework, dashboards, and operating reviews for SpecOps OpEx and AI programs (e.g., LTV loss avoided, DSAT/CSAT, recontact rate, AHT, time‑to‑resolution, fraud/abuse reduction, agent time saved, adoption and MAU of AI tools). • Codify governance and change management: Define guardrails, documentation standards, and enablement for AI solutions (playbooks, SOPs, micro‑trainings) so that changes are safe, compliant, well‑understood by frontline teams, and adopted at scale.