Director, AI Infrastructure Strategy & Operations - AI Experiences

Microsoft•Redmond, WA

39d•$155,800 - $303,600

About The Position

Microsoft AI Experiences (AIX) is building AI experiences across Copilot, Bing, Edge, and partner surfaces. As a leader in the AIX Strategy organization, this role shapes how AIX plans, allocates, and manages the infrastructure that powers its AI experiences. The position leads cross-functional planning and decision-making for GPU capacity and related infrastructure investments, working with Product, Engineering, Finance, and Infrastructure teams. It develops forecasting models, resource-allocation frameworks, and infrastructure governance, ensuring capacity investments align with business priorities and product outcomes. The role requires strategic thinking, quantitative rigor, business judgment, operational excellence, and the ability to communicate recommendations to senior executives. AI Experiences employees who live within a 50-mile commute of a designated Microsoft Hub in the U.S. are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Requirements

Master's degree in Business, Economics, Finance, Engineering, Computer Science, Data Science, or a related field and 6+ years of experience in strategy, business planning, finance, product management, operations, or program management; or bachelor's degree in one of these fields and 8+ years of relevant experience; or equivalent experience.
6+ years of experience with AI infrastructure, cloud capacity planning, model serving, inference, training, or distributed systems.
6+ years of experience building business cases and ROI models for technology investments.
6+ years of experience partnering closely with Product, Engineering, and Finance organizations.
6+ years of experience with SQL, Python, Power BI, Kusto, Excel, or other analytical tools.
Experience operating in fast-paced, highly ambiguous environments and creating structure where processes do not yet exist.

Nice To Haves

Master's degree in Business, Economics, Finance, Engineering, Computer Science, Data Science, or a related field and 12+ years of experience in strategy, business planning, finance, product management, operations, or program management.
6+ years of experience in Strategy, Management Consulting, and/or Finance.
Experience with AI infrastructure, cloud capacity planning, model serving, inference, training, or distributed systems.
Experience building business cases and ROI models for technology investments.
Experience partnering closely with Product, Engineering, and Finance organizations.
Experience with SQL, Python, Power BI, Kusto, Excel, or other analytical tools.
Experience operating in fast-paced, highly ambiguous environments and creating structure where processes do not yet exist.

Responsibilities

Lead forecasting and planning for GPU capacity and other AI infrastructure resources across AIX.
Develop demand models incorporating product roadmaps, user growth, model transitions, workload characteristics, and migration plans.
Create and maintain frameworks for evaluating, prioritizing, and allocating constrained infrastructure resources across products and business priorities.
Drive governance processes for infrastructure requests, allocation decisions, escalations, and executive reviews.
Partner with Product, Engineering, Infrastructure, and Finance teams to connect infrastructure investments to business outcomes, including engagement, quality, revenue, efficiency, and customer experience.
Build quantitative models, scenario analyses, and business cases to support investment and resource-allocation decisions.
Define and improve telemetry, reporting, and dashboards for infrastructure utilization, capacity, throttling, costs, and business impact.
Lead cross-organizational initiatives involving infrastructure migrations, workload transitions, capacity reallocations, and cost-optimization efforts.
Identify capacity risks early and develop mitigation strategies that preserve business objectives while improving efficiency.
Translate complex technical and operational information into clear recommendations and executive-ready communications.