Global Service Manager AMS – AI Ops and CSI

Job Description Summary
Sandoz continues to go through an exciting and transformative period as a global leader and pioneering provider of sustainable Biosimilar and Generic medicines. As we continue down this new and ambitious path, unique opportunities will present themselves, both professionally and personally. Join us, the future is ours to shape!

As the Global Service Manager, AI Ops and CSI, you will be responsible for driving proactive, data-driven Application Management Services (AMS) operations through AI-powered service management, automation and continuous improvement initiatives. The role partners closely with business stakeholders, application owners, infrastructure teams and AMS providers to improve service quality, operational efficiency and user experience across the global application landscape.

Job Description
Your Key Responsibilities:

Lead AI Ops and Continual Service Improvement (CSI) across the global AMS portfolio to enable proactive, data-driven operations, intelligent automation and measurable improvements in service quality, efficiency and user experience.

- Own the AI Ops and CSI strategy, operating framework and governance cadence across in-scope applications and AMS providers; define priorities, decision rights, delivery standards and escalation routes aligned to business needs and approved service commitments.

- Build and govern a prioritised AI Ops use-case pipeline covering anomaly detection, event correlation, alert-noise reduction, incident classification and routing, knowledge recommendations and assisted root-cause analysis; assess data readiness, feasibility, expected value and delivery effort before progressing from pilot to scale.

- Coordinate application owners, EAS, Infrastructure and AMS providers to establish actionable observability across application logs, metrics, events and service dependencies; govern data quality, contextual enrichment and integration with monitoring, ITSM and configuration records to support reliable operational insights.

- Drive proactive incident and problem management through AI-assisted triage, impact assessment, trend analysis and identification of recurring issues; ensure insights translate into owned corrective actions, improved knowledge articles and permanent fixes, with operational teams validating recommendations before execution.

- Govern intelligent automation for repetitive support activities, service requests, diagnostics and approved remediation runbooks; require clear ownership, access controls, testing, exception handling, human approval where appropriate and change-controlled deployment, and measure reductions in manual effort and processing time.

- Own a consolidated CSI register and rolling improvement roadmap, drawing on service reviews, incident and problem trends, SLA performance, user feedback and delivery bottlenecks; define each initiative’s problem statement, baseline, target outcome, accountable owner, milestones, dependencies and acceptance criteria.

- Lead cross-functional improvement delivery with business stakeholders, application owners, EAS, Infrastructure, Quality and AMS providers; remove process hand-off gaps, standardise support practices, manage dependencies and escalate overdue actions, while keeping initiatives within approved capacity and commercial scope.

- Establish baselines and dashboards for incident recurrence, mean time to detect and resolve, alert quality, automation adoption, request turnaround, SLA attainment and user experience; validate realised benefits against agreed measures, distinguish released capacity from cash savings and use results to reprioritise the roadmap.

- Maintain clear accountability boundaries: this role governs the AMS AI Ops and CSI roadmap, outcomes and provider commitments; application owners approve application-specific requirements and acceptance; platform teams own enabling technology; AMS providers implement and operate approved capabilities; designated governance and Quality functions approve applicable controls.

Key performance indicators:

- AI Ops adoption and coverage: proportion of prioritised use cases deployed and actively used, and in-scope applications with actionable observability and validated operational data, measured against agreed roadmap targets.

- Alert quality and incident response: reduction in duplicate and non-actionable alerts, improved incident classification and routing accuracy, and reduced mean time to detect and resolve incidents against agreed service baselines.

- Automation effectiveness: proportion of eligible support activities automated, successful execution rate, reduction in manual effort and request turnaround time, and exception rates within agreed thresholds for approved workflows.

- Recurring-incident reduction: decrease in repeat incidents for prioritised problem areas, timely closure of root-cause corrective actions and sustained effectiveness of permanent fixes against agreed baseline and review periods.

- CSI roadmap delivery: proportion of prioritised initiatives completed on time and accepted against agreed outcomes, with current baselines, accountable owners and benefits measures; reduction in overdue milestones and improvement actions.

- Realised service and business benefits: validated improvements in SLA attainment and user satisfaction, released support capacity and cost efficiency against agreed baselines and targets, with released capacity reported separately from realised cash savings.

Minimum Requirements:
Education

Degree in IT, Computer Science, Engineering, Data Science or equivalent; ITIL Foundation required. Advanced certification in IT service management, continual improvement, AI Ops, data analytics, automation or cloud operations desirable.

Languages
Fluent written and spoken English.

Experience & Skills

- 10+ years in IT, including 5+ years in application service management, operational improvement, intelligent automation or regulated managed-service delivery, with practical experience applying AI Ops and CSI.

- Proven global, multi-supplier governance of AI Ops use cases and CSI roadmaps, including prioritisation, baseline definition, delivery oversight, adoption and measurable benefits realisation.

- Strong ITIL incident, problem, change, release, service-level and continual-improvement knowledge; experience with ServiceNow, CMDB, observability, event-management and automation platforms.

- Strong analytical judgement, supplier management, improvement facilitation, change adoption, executive communication and cross-functional leadership; ability to translate operational insights into prioritised actions and demonstrate improvements in service quality, efficiency and user experience.

Skills Desired
Agile Project Management, Business Partnering, Change Management, IT Service Delivery, Performance Management