Head of L&H – Transversal Services / Platforms

Cloud platform and platform engineering leadership

• Oversee the evolution of the DSCP platform as a modern multi-cloud engineering platform leveraging infrastructure-as-code, Terraform, and managed/PaaS capabilities.

• Ensure the platform operating model supports secure onboarding, reusable components, guardrails, observability, and production readiness.

• Drive alignment between platform architecture, cloud governance, security requirements, and delivery team enablement.

• Promote shared standards for platform modules, deployment patterns, environment provisioning, and lifecycle management.

Frontend framework, design system, and AI-enabled SDLC

• Lead the shared frontend framework capability as a strategic enabler for consistency, speed, accessibility, and maintainability across products.

• Ensure alignment with the SCOR Design System, shared component models, and modern frontend engineering standards.

• Drive the evolution of AI-enabled frontend and development workflows, including the integration of design, documentation, task management, and engineering execution where they create real value.

• Strengthen the role of shared frontend capabilities as a bridge between design, engineering, and product delivery.

Digital Experience, developer tooling, and productivity services

• Oversee the Digital Experience agenda across developer tooling, platform enablement, digital workplace support, Mac lifecycle management, Atlassian ecosystem enablement, FinOps-related enablement, and internal engineering productivity.

• Improve the quality, simplicity, and scalability of the internal technology experience for engineers and related teams.

• Standardize tooling and workflows where beneficial, while reducing friction, duplication, and operational overhead.

• Ensure internal tooling and productivity services support secure, compliant, and high-velocity engineering work.

Operational support excellence and SLA-driven service management

• Lead the evolution of L2 operational support capabilities toward a more mature, transparent, and performance-driven support model.

• Strengthen incident, request, escalation, and service support practices in line with agreed SLAs and operational expectations.

• Improve production readiness, service observability, support handoffs, and operational governance.

• Drive standardisation of support metrics, issue prevention, and continuous service improvement.

AI, automation, and efficiency at scale

• Promote practical and disciplined use of AI to improve platform engineering, service operations, developer productivity, internal support, and workflow automation.

• Identify high-value use cases for automation and AI-assisted operations, such as audit support, support automation, engineering enablement, documentation, and workflow orchestration.

• Ensure AI adoption is governed, measurable, and integrated into sustainable operating practices rather than treated as experimentation alone.

• Drive a culture where teams use automation to remove repetitive work and focus on higher-value engineering and operational outcomes.

Financial discipline, vendor management, and platform economics

• Bring strong oversight to platform cost management, tooling spend, cloud/platform economics, and vendor/service trade-offs.

• Work closely with relevant stakeholders on FinOps-related transparency, cost allocation, and consumption optimisation.

• Ensure platform and transversal services are run with sound economics, clear ownership, and value-oriented prioritisation.

• Manage strategic external partners and internal service dependencies with clear accountability and outcome focus.

Cross-team integration and engineering coherence

• Work closely with the Heads of Engineering and other technology leaders across L&H and SCOR to ensure transversal services actively enable—not slow down—delivery.

• Connect platform engineering, frontend foundations, tooling, workplace, and support capabilities into one coherent internal platform strategy.

• Eliminate fragmentation, duplicated tooling patterns, and local optimisations that damage scale or maintainability.

• Help establish best-in-class engineering practices across shared services and platform domains.

• Commercial and financial awareness, including platform/tooling economics and FinOps-related thinking

• A pragmatic but ambitious approach to AI-enabled engineering and automation

• Strong communication and stakeholder management skills across engineering, architecture, security, operations, and senior leadership

Preferred skills :

• Significant experience in software engineering and senior technology leadership, including leadership of shared platforms or transversal technology capabilities

• Proven experience leading one or more of the following at meaningful scale:

• platform engineering / cloud platforms

• developer experience / engineering productivity

• internal tooling and shared frameworks

• support / service operations / production enablement

• Strong understanding of modern cloud platforms, infrastructure-as-code, Terraform, automation, APIs, observability, security, and platform operating models

• Strong understanding of software development lifecycle practices, Agile/DevOps ways of working, and engineering quality disciplines

• Experience leading shared frontend/platform capabilities or design-system-aligned engineering is a strong advantage

• Experience in service-oriented support models, operational excellence, support automation, or SLA-driven environments is highly valuable

• Experience managing cloud/tooling cost transparency, internal service economics, or FinOps-related topics is preferred

• Practical understanding of AI/LLM opportunities in engineering, operations, and internal productivity services

• Experience in regulated environments is an advantage