Global Service Manager AMS - AI Ops and CSI

(FCRS = BR012) SANDOZ DO BRASIL IND FARMACEUTICA LTDA; Telangana; On-site; INR 4,500,000 - 6,500,000; Full time

Job summary

Sandoz do Brasil Ind Farmaceutica LTDA is seeking a senior AI Ops/CSI leader to drive proactive, data-driven operations and automation across the AMS portfolio. Based in Telangana, this role focuses on building a scalable observability framework, governance cadence and continual service improvements across global applications.

You will coordinate cross-functional teams including application owners, EAS, Infrastructure and AMS providers to reduce incident impact and improve service quality

Responsibilities

• Lead AI Ops and CSI across the global AMS portfolio to enable proactive, data-driven operations and intelligent automation.
• Own the AI Ops and CSI strategy, governance cadence, and delivery standards across in-scope applications and AMS providers.
• Build and govern an AI Ops use-case pipeline including anomaly detection, alert-noise reduction, and root-cause analysis.
• Coordinate owners, EAS, Infrastructure and AMS providers to establish actionable observability across logs, metrics and service dependencies.
• Drive proactive incident and problem management with AI-assisted triage and validated corrective actions.

Job description

Job Description

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!

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 elevate 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