• Define and own the enterprise decisioning charter, objectives, operating model, guardrails (e.g., prospect and existing client fatigue, fairness, privacy), and KPI trees aligned to strategic business outcomes. • Establish and govern the enterprise roadmap for the decision engine, including prioritization of NBA and lead-routing initiatives in partnership with Sales, Marketing, Product, Technology, and Client Services. • Balance delivery commitments, technical constraints, and strategic trade-offs while communicating clear timing, dependencies, and risks to executive stakeholders. • Maintain end-to-end accountability for the architecture, build, performance, governance, and lifecycle management of a real-time decision engine powering NBA decisions and decision sequences at scale. • Direct teams responsible for translating enterprise goals (e.g., sales growth, engagement, retention) into eligibility schemas, fatigue and frequency limits, fairness constraints, reward functions, and constrained optimization approaches (assignment, pacing, routing). • Oversee the design and deployment of decision policies, optimization frameworks, and sequencing logic that deliver the best action or action sequence for each prospect or existing client. • Establish standards for experimentation, rollout, and risk management, incorporating canaries, bandit approaches, A/B testing, and statistically sound ship/iterate/stop decisions. • Partner with personalization, experimentation, and analytics leaders to co-own experimentation strategy, learning agendas, and measurement frameworks. • Lead cross-functional technology delivery by setting requirements and direction for real-time decision APIs, integrations, rules engines, data models, and logging frameworks. • Ensure enterprise standards for versioning, audit trails, rollback and disaster recovery plans, incident response, and service-level agreements. • Maintain canonical decision metrics, fairness and eligibility checks, transparent decision logs, and audit-ready documentation to support reporting, regulatory review, and internal governance. • Build, lead, and develop a team of Decision Science and Technical Product Management leaders; set expectations, coach performance, and grow enterprise decisioning capabilities.