Director, Global Black Belt

Microsoft•,

7d•$133,000 - $239,800

About The Position

The Director, Global Black Belt leads the Americas AI+Data team of technical sales and solution leaders, accelerating customer adoption of Microsoft’s AI platform and guiding strategic, complex customer transformations. The role combines technical and market understanding with customer leadership, business acumen, and organizational leadership. The Director builds and develops a high-performing GBB team, engages with executive customers, and partners across Sales, Engineering, Product, Customer Success, and the partner ecosystem. The position focuses on helping customers move from AI experimentation to production-scale adoption, translating Microsoft product innovation into customer outcomes and repeatable go-to-market motions. It also turns insights from strategic engagements into reusable technical assets and programs, brings customer and field feedback to Product and Engineering, and shapes an AI-first operating model for the organization. The role requires strategic leadership, technical credibility, talent development, operational discipline, and the ability to influence across organizational boundaries.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Business Administration, Information Security, or a related field, and 8+ years of experience in technical solution architecture and enterprise sales, business development, strategic consulting, technical consulting, or a relevant/prioritized industry; or equivalent experience.
Ability to provide proof of citizenship, U.S. permanent residency, or other protected status for export-controlled information access eligibility; citizenship will be verified with a valid passport, with other applicable documents permitted for lawful permanent residents, refugees, and asylees.
Technical and AI fluency sufficient to guide teams, challenge assumptions, and engage sophisticated customers on cloud, data, applications, foundation models, agents, and AI platforms.
Ability to engage senior customer executives, build trusted relationships, and connect technical strategy to customer outcomes.
Leadership capabilities in strategy, talent development, change leadership, communication, collaboration, and organizational execution.

Nice To Haves

12+ years of experience across enterprise technology, cloud, AI, technical sales, solution engineering, product, consulting, or related disciplines.
Experience leading high-performing technical, sales, solution, engineering, or customer-facing teams.
Experience driving large and complex enterprise technology transformations.
Understanding of cloud computing, modern application platforms, data, generative AI, AI agents, and emerging enterprise AI architectures.
Experience engaging and influencing C-level business and technology executives.
Experience translating complex technology into business value and measurable customer outcomes.
Experience leading complex customer opportunities involving multiple technologies, stakeholders, partners, and organizational boundaries.
Experience creating scalable programs, technical solutions, intellectual property, or go-to-market motions from individual customer engagements.
Business and commercial acumen connecting technical strategy to adoption, consumption, and growth.
Experience influencing Product and Engineering with structured customer evidence and market insights.
Experience leading organizational or business transformation through significant technology or market change.
Understanding of competitive dynamics across cloud and AI platforms.
Communication, executive presence, and relationship-building skills.
Analytical and operational management experience spanning strategic thinking and detailed execution.
Leadership experience in enterprise AI, cloud platforms, developer platforms, data platforms, or AI applications.
Experience with Microsoft Azure and Microsoft’s AI platform, including Microsoft Foundry and the broader Microsoft AI ecosystem.
Experience designing or deploying generative AI and agentic AI solutions in enterprise production environments.
Experience building or leading specialized technical sales, solution engineering, consulting, or field engineering organizations.
Experience taking emerging technologies from early customer adoption to repeatable, scaled field execution.
Experience creating technical IP, accelerators, architectures, or field programs scaled across multiple customers or regions.
Experience working closely with engineering and product teams to translate customer requirements into product improvements.
Experience leading transformation across a large, matrixed global organization.

Responsibilities

Engage senior business and technology executives to shape cloud and AI strategies and identify opportunities for meaningful business impact.
Lead technical strategy for strategic and complex AI opportunities, helping customers move from experimentation and proof of concept to production-scale adoption.
Understand customers’ business priorities, technology landscapes, regulatory requirements, and industry dynamics.
Help customers reimagine applications and business processes around generative AI, agents, data, and cloud platforms.
Act as a trusted advisor on emerging technology choices and architectural decisions.
Drive adoption and consumption of Microsoft Cloud & AI Platforms through high-impact customer engagements.
Translate Microsoft product innovation into customer scenarios and repeatable go-to-market motions.
Help remove technical, architectural, commercial, and organizational barriers to production AI adoption.
Partner with account teams to identify opportunities, develop technical strategies, and advance complex opportunities through the sales and adoption life cycle.
Maintain focus on measurable customer outcomes and sustainable platform consumption.
Attract, develop, and retain technical and business talent, and build a leadership bench.
Coach leaders and individual contributors to work effectively with customer executives, account teams, product groups, and engineering organizations.
Foster customer obsession, technical depth, accountability, inclusion, collaboration, and continuous learning.
Build mechanisms that turn individual customer expertise into organizational capability.
Convert strategic engagement learnings into reusable architectures, playbooks, demonstrations, accelerators, technical patterns, and sales motions.
Identify cross-customer and industry patterns that can become repeatable solutions and field programs.
Share best practices and technical insights across the Microsoft field and partner with relevant organizations to scale successful customer patterns.
Create feedback loops among customers, the field, Product, and Engineering; identify recurring product gaps, blockers, competitive challenges, and emerging requirements.
Provide evidence-based customer signals to inform product and engineering priorities, and partner with Engineering to resolve critical blockers and improve product readiness.
Champion an AI-first approach to technical sales and customer engagement, including AI-assisted and agent-driven workflows.
Develop approaches to scale technical expertise across customers, sellers, partners, and geographies, and lead organizational change for a rapidly evolving AI market.
Establish organizational priorities, objectives, and metrics, and maintain operational discipline across pipeline, engagements, adoption, consumption, blockers, and outcomes.
Focus resources on high-impact opportunities, use data and customer evidence to improve execution, and influence outcomes across organizational boundaries.