Cloud Service Delivery Manager, Data & AI Platforms (Azure)

5+ years of experience in IT Service Management (ITSM), Cloud Operations, or Technical Program/Portfolio Management within a complex enterprise environment.

Solid foundational understanding of multi-cloud environments (AWS, Azure, and GCP) to confidently discuss infrastructure and integration needs with internal customer teams.

Proven track record of managing and improving multi-service help desks, ticketing workflows (e.g., GitHub Projects, Jira Service Desk, ServiceNow), and establishing SLA/OLA frameworks. - Strong financial acumen with hands-on experience in multi-cloud cost management, budgeting, and FinOps methodologies.

Excellent stakeholder management skills, with experience navigating complex enterprise governance, risk, and compliance frameworks (e.g., working with security, legal, and audit teams).

Outstanding communication and interpersonal skills, with the ability to translate complex multi-cloud, regulatory, or technical requirements into business-friendly terms.

Direct experience working with FinOps methodologies or holding a FinOps Certified Practitioner credential.

Familiarity with multi-cloud billing tools, cloud budgeting software, or SaaS consumption tracking tools.

Strategic understanding of the enterprise AI operating layer, including LLM Gateways, specialized GCP architectures (Gemini, Vertex, Agents), and AI observability tools (such as Arize)

Portfolio Service Delivery & Support Excellence: Own the end-to-end customer support lifecycle for our entire Enterprise AI portfolio. Establish, monitor, and continuously improve support processes, ticket resolution times, and customer satisfaction metrics to ensure internal Siemens teams receive world-class, unified support across all services.

Financial Management & Portfolio FinOps: Act as the financial custodian of the portfolio. Own multi-vendor budget forecasting, track monthly actuals versus budgets, manage the internal chargeback/showback mechanisms, and partner with engineering to execute cost-optimization opportunities across hyperscalers (AWS, Azure, GCP) and SaaS models (OpenAI, Gemini Enterprise).