Director: AI Ops, Incident Management, Problem Management and Level 2 Application Support

Director: AI Ops, Incident Management, Problem Management and Level 2 Application Support

We are seeking an experienced and dynamic Vice President - Director responsible for AI Operations, Incident Management, Problem Management and Level 2 Application Support. This senior leader will be accountable for the strategy, execution, and continuous improvement of enterprise Incident Management, Problem Management, and Level 2 Application Support capabilities with a desired outcome of minimizing incidents and maximizing service availability.

The ideal candidate will possess a strong technology operational leadership background and a passion for building modern, proactive operations organizations that leverage automation, observability, artificial intelligence, and data-driven decision-making.

This leader will drive the transformation from reactive support models toward predictive and preventative operations through the adoption of AI Ops, intelligent automation, and continuous service improvement practices.

This role will partner closely with Engineering, Infrastructure, Architecture, Cybersecurity, Product, and Business stakeholders to improve operational resilience, reduce customer-impacting incidents, accelerate restoration times, eliminate recurring issues, and enhance the overall customer and team member experience.

• Define and execute the enterprise strategy and roadmap for Incident Management, Problem Management, and Level 2 Application Support.
• Establish a long-term vision for operational excellence, resiliency, service restoration, and issue prevention.
• Develop and maintain organizational goals, key performance indicators (KPIs), and operational maturity targets.
• Ensure alignment between operational priorities, business objectives, customer experience goals and technology strategy.

• Provide executive leadership and governance for major incident management across the enterprise.
• Establish and continuously improve incident response processes, escalation procedures, communication standards, and operational playbooks.
• Ensure rapid and effective coordination across Technology teams during critical incidents.
• Drive improvements in Mean Time to Detect (MTTD), Mean Time to Restore Service (MTTR), customer impact measurement, and incident communications.
• Partner with Observability, Monitoring, Infrastructure, and Application teams to improve detection, diagnosis, and recovery capabilities.
• Lead executive communications during significant customer or business impacting events.

• Own the enterprise Problem Management practice and associated governance.
• Establish rigorous root cause analysis standards and ensure corrective actions are identified, prioritized, and completed.
• Analyze operational trends, recurring incidents, and systemic risks to identify opportunities for stability improvements.
• Drive initiatives that eliminate recurring issues, reduce operational toil, and improve overall platform reliability.
• Develop reporting and executive dashboards that measure problem trends and remediation effectiveness.
• Foster a blameless culture focused on prevention rather than reaction.

• Provide leadership for Level 2 Application Support teams responsible for diagnosing, troubleshooting, and restoring application services.
• Establish support models, staffing strategies, and operational procedures aligned to business priorities and customer outcomes.
• Ensure Standard Operating Procedures (SOPs), knowledge articles, runbooks, and troubleshooting guides remain current and effective.
• Partner closely with Level 3 Engineering teams to improve supportability, logging, instrumentation, diagnostics, and operational readiness.
• Ensure support teams are prepared to support new technologies, platforms, and application releases.
• Drive consistency and excellence across all application support functions.

• Develop and execute an enterprise AI Ops strategy that transforms incident detection, diagnosis, correlation, prediction, and remediation.
• Leverage machine learning, event correlation, predictive analytics, and automation technologies to identify operational issues before customer impact occurs.
• Drive adoption of intelligent alerting, automated triage, automated root cause identification, and self-healing capabilities.
• Partner with Observability, Engineering, and Data teams to build operational intelligence platforms that reduce noise, improve signal quality, and accelerate resolution.
• Identify opportunities to automate repetitive support, incident response, and problem management activities through workflows, orchestration, scripting, and AI-enabled solutions.
• Establish measurable targets for automation adoption, operational efficiency, incident reduction, and support productivity improvements.
• Continuously evaluate emerging AI, automation, and operational technologies to enhance…