AI Support Manager

About the role

Gallagher is looking for an experienced AI Support Manager to lead the operational support and maintenance of enterprise AI platforms, applications and services. The role manages day-to-day support of AI systems, oversees ticket triage and resolution, and acts as the main link between AI Product, AI Engineering and business stakeholders. It requires US business hours and the ability to work according to the assigned US time zone.

Key responsibilities

• Manage operational support of AI applications, services and platforms, ensuring availability, performance and reliability through proactive monitoring and issue management
• Lead incident, problem and service request management for AI solutions and coordinate troubleshooting of complex technical issues
• Oversee intake, prioritization, assignment and escalation of tickets from AI Product and AI Engineering teams
• Establish and maintain SLAs, KPIs and support metrics, monitor support queues and drive continuous improvement of support processes
• Manage and mentor a team of support analysts and engineers, provide coaching and performance management, and coordinate shift coverage and resource planning

Required profile

• Bachelor's degree in Computer Science, Information Technology, Engineering or a related field
• 10+ years of IT experience in application support, production support or technical operations
• 3+ years of supervisory or people management experience, including managing support teams in a fast-paced environment
• Strong understanding of incident, problem and change management processes
• Experience with AI/ML-powered applications, intelligent automation platforms or emerging AI technologies

Required skills

• Ticketing and service management tools such as ServiceNow, Jira or similar
• Analytical, troubleshooting and decision-making abilities
• Excellent communication and stakeholder management skills
• Preferred: experience with Generative AI, ML or enterprise AI; ITIL Foundation or higher; cloud platforms such as Azure, AWS or Google Cloud; monitoring, observability and application performance tools; DevOps, MLOps or AI Operations exposure