Director, AI Infrastructure Strategy & Operations - AI Experiences

Microsoft•Redmond, WA

1d•$155,800 - $303,600•Hybrid

About The Position

Microsoft AI Experiences (AIX) is building the future of AI experiences across Copilot, Bing, Edge, and partner surfaces that reach hundreds of millions of people. As AI products grow in reach and sophistication, access to compute and infrastructure is increasingly central to product strategy, customer experience, and business performance. This role sits within the AIX Strategy organization and will lead cross-functional planning and decision-making for GPU capacity and related infrastructure investments. Working across Product, Engineering, Finance, and Infrastructure teams, you will develop forecasting models, establish resource-allocation frameworks, drive infrastructure governance, and ensure capacity investments are aligned to business priorities and product outcomes. The ideal candidate combines strong strategic thinking, quantitative rigor, business judgment, and operational excellence. They are equally comfortable discussing infrastructure constraints with engineering teams, evaluating business tradeoffs with finance partners, and presenting recommendations to senior executives.

Requirements

Master's Degree in Business, Economics, Finance, Engineering, Computer Science, Data Science or related field AND 6+ years experience in strategy, business planning, finance, product management, operations, or program management, OR Bachelor's Degree in Business, Economics, Finance, Engineering, Computer Science, Data Science or related field AND 8+ years of experience in strategy, business planning, finance, product management, operations, program management 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 related field AND 12+ years of experience in strategy, business planning, finance, product management, operations, or program management
6+ years experience in Strategy, Management Consulting, and/or Finance.
6+ years of 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 that incorporate 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 the telemetry, reporting, and dashboards required to understand 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.