Director - MES, Engineering, EHS & Sustainability

Overview

Lead operational stability, service governance and continuous improvement across GSK's MES, Engineering, EHS & Sustainability platforms, acting as the primary escalation point for platform issues and partnering with Product Owners, architects and engineering teams.

What you'll do

• Provide operational leadership across core platforms, ensuring system stability, availability and adherence to service levels, and act as the primary internal escalation point for major incidents.
• Govern incident, problem, change, configuration and release processes for domain platforms, ensuring compliance with ITSM policies and control frameworks, and define measurable problem management outcomes (e.g., RCA closure time, recurrence prevention, defect trend reduction).
• Define and maintain service readiness and runbook quality standards, ensuring escalation paths, support tasks, data handling, continuity steps and deployment impacts are validated before go-live.
• Set the service vision and roadmap for the domain platforms with the Product Owners, and own the value case for service improvements with measures agreed up front.
• Create and oversee service plans for new and enhanced products, coordinating with Product Owners, third-party partners and platform/service teams to define SLAs, performance expectations and support handover criteria.
• Monitor platform performance, proactively identify risks, trends and recurring issues, and implement improvement actions to strengthen stability and user experience.
• Coach service owners and operations staff in incident, problem and change practice and set practice standards across the domain.
• Report platform adoption and business-outcome measures alongside service KPIs, and agree improvement targets with the Product Owners.
• Coordinate with Platform Owners, engineering squads, solution architects and service teams to ensure changes, integrations, upgrades and releases are deployed safely and meet operational readiness standards.
• Lead operational readiness assessments, ensuring documentation, support models, monitoring coverage and non-functional controls are in place prior to deployment.
• Own operational dashboards, KPIs and reporting for the platforms, communicating performance, risks and issues to senior stakeholders.
• Oversee root cause analysis for major incidents, ensuring sustainable fixes, clear remediation actions and preventative measures are identified and delivered.
• Maintain and continuously improve operational documentation, including runbooks, support procedures, configuration inventories and architectural operational views.
• Manage relationships with third-party vendors and managed service providers to ensure high-quality operational support and fulfilment of contractual obligations.
• Scan emerging service-management and monitoring capability, trial the best candidates and bring a ranked opportunity list into the product roadmap.
• Own the operational service model for production AI and generative AI solutions, including support tiers, escalation paths, service levels, runbooks and supplier responsibilities.
• Define and approve AI service-readiness criteria before go-live, covering monitoring, support, security, data handling, continuity, rollback and human-oversight arrangements.
• Govern incidents, problems, changes, releases and configurations involving AI models, prompts, knowledge sources, integrations and platform components.
• Ensure AI-specific service risks and failures, such as unsupported outputs, retrieval failures, model degradation and inappropriate data exposure, are investigated and sustainably remediated.
• Lead your team in using approved AI tools to improve productivity and ways of working, role-modelling responsible use and following GSK's Responsible AI, privacy and security requirements.

What you'll need

• Bachelor's or Master's degree in a relevant field (e.g., Computer Science, Information Technology, or Systems Engineering), or equivalent experience.
• Typically 8–10 years of experience in platform operations, system administration, service management, or technical delivery roles within complex environments.
• Platform operations, service management, ITSM processes, cloud technologies and core enterprise system administration.
• Understanding of system integration, monitoring and operational control frameworks.
• Working knowledge of MES, engineering or EHS & Sustainability processes and how users depend on the platforms.
• Significant experience overseeing operational performance for multiple platforms or systems within a complex environment.
• Demonstrated ability to manage ITSM processes, including incident, problem, change, release and configuration management.
• Proven ability to diagnose operational issues, lead root cause analysis and drive sustainable improvements.
• Experience coordinating with engineering, architecture and product teams to ensure operational readiness and safe deployment of changes.
• Experience producing and maintaining operational artefacts such as runbooks, support procedures and readiness assessments.
• Familiarity with operational KPIs, risk indicators, monitoring dashboards and performance reporting.
• Experience operating in Agile and/or DevOps environments supporting continuous delivery and operational stability.
• Experience managing the operation or support of production AI, machine-learning, advanced analytics or data-intensive services.
• Experience defining operational-readiness and support requirements for AI-enabled solutions before production release.
• Experience leading major incidents and root-cause investigations involving applications, AI services, data, integrations or cloud platforms.
• Experience governing changes to AI models, prompts, knowledge sources, orchestration logic or related integrations.
• Experience managing specialist suppliers, cloud providers or managed service partners supporting AI-enabled platforms.

Nice to have

• Industry certifications highly desirable (e.g., ITIL, Agile/Scrum, Service Management, DevOps Foundations).
• Strong analytical and problem-solving capability, especially in complex operational scenarios.
• Excellent communication and stakeholder management skills, with the ability to provide clarity during incidents and complex change cycles.
• Strong understanding of security, compliance and operational risk controls.
• Ability to lead cross-functional teams, influence without direct authority and promote operational discipline.
• Effective organisational skills, able to balance multiple priorities and manage time-sensitive escalations.
• Practical understanding of generative AI, large language models, machine learning and retrieval-augmented generation, sufficient to manage their operation and associated service risks.
• Understanding of AI service monitoring, including the distinction between conventional platform availability and the ongoing quality of AI-generated outputs.
• Ability to apply ITSM disciplines to AI services, including incident, problem, change, release, configuration and knowledge management.
• Strong understanding of responsible AI, cybersecurity, privacy, data integrity, human oversight and access-control requirements.
• Ability to interpret AI service metrics, logs, evaluation results and user feedback to identify deterioration, recurring failures and improvement priorities.

Details

• Location: Bengaluru Luxor North Tower.