infinitus - Operations Manager, Digital Hub

• Launch Stabilization & Daily Operations • Tactical Execution & Stabilization: Actively monitor the "virtual floor," dive into the granular details of complex escalations, and personally troubleshoot workflow bottlenecks to ensure a rapid and smooth transition from launch to steady-state operations. • Operational Oversight: Direct the day-to-day operations of the Hub, managing efficient workflow distribution across AI systems and teams while maintaining a constant, hands-on presence to quickly address immediate launch challenges. • Seamless Handoffs: Personally investigate friction points in routing protocols between AI agents and human staff, rapidly iterating to minimize disruptions during escalations and complex case transfers. • Resource Allocation: Monitor real-time volume across both digital (AI) and traditional channels, jumping into the queues to assess reality on the ground and adjusting human staffing assignments to handle escalations during peak periods. • Team Leadership & Development • In-the-Weeds People Management: Direct, coach, and mentor a team of frontline supervisors, team leads, and human-in-the-loop specialists by leading from the front, participating in side-by-side shadowing, and directly handling edge cases when necessary. • Human-AI Collaboration: Foster a culture where human staff effectively leverage AI tools. Train employees on how to interact with, monitor, and provide corrective feedback to AI systems based on your own hands-on experience with the tools. • Continuous Tuning: Partner with technical and operational teams to continuously review AI transcripts and outcomes, utilizing your deep, ground-level understanding of the daily workflow to provide the business logic needed to improve AI accuracy and empathy. • Performance Management & Reporting • Comprehensive SLA Attainment: Ensure the program consistently meets or exceeds SLAs across all channels. Track traditional metrics (Average Handle Time, Abandonment Rate) and AI-specific metrics (Containment Rate, Deflection Rate, AI-to-Human Escalation Accuracy). • Root Cause Data Analysis: Leverage analytics dashboards to identify trends, digging deep into the root causes of early operational hiccups and translating data into immediate, tactical operational fixes. • Cross-Functional Collaboration: Partner effectively with Product Operations, QA, Learning & Development, Product, and AI/Automation engineers to ensure program alignment, swift issue resolution, and the rapid deployment of necessary system patches during the stabilization phase. • Compliance & Quality Assurance • Regulatory Adherence: Ensure all program activities—whether executed by a human or an AI agent—strictly comply with HIPAA, OIG guidelines, and client-specific business rules. • Adverse Event Management: Guarantee that AI agents are properly trained to identify and flag potential Pharmacovigilance (Adverse Event and Product Quality Complaint) triggers for immediate human review and reporting. • Quality Partnership: Collaborate with the QA/QC team to review audit trends across human and AI interactions, implementing corrective actions (CAPAs) to quickly refine both human training and AI algorithms.