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# Principal AI Delivery Acceleration Consultant - Cloud Computing

- **Company:** Amazon.com, Inc.
- **Location:** Chicago, IL, United States
- **Salary:** $210,000.0 - $240,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Data Driven Tests, Data Analytics
- **Published:** October 19, 2026
- **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=3026984322-2

## About the Role

* Cloud computing (AWS)
 * AI/ML solution design
 * Strategic program management
 * AI Development Lifecycle (AIDLC)
 * Stakeholder management
 * Business outcome measurement
 * Data-driven process improvement
 * Technical writing (PRFAQ/narratives)
 * Professional services delivery models
 * Change management

## Description

The Principal AI Delivery Acceleration Consultant leads strategic initiatives that transform how AWS Professional Services sells and delivers cloud engagements. You will define vision and roadmaps, rapidly prototype AI-powered solutions, and transition them into scalable offerings. The role involves partnering across business and technical teams, influencing senior stakeholders, measuring portfolio-level outcomes, and driving continuous improvement in global delivery methods and automation., * Own and drive strategic AI delivery initiatives from inception through global scaled adoption.

 * Define initiative vision, success metrics, and roadmaps using working-backwards narrative methods (PRFAQ).
 * Rapidly prototype AI-powered solutions using the AI Development Lifecycle and deliver in short sprints.
 * Transition prototypes and beta solutions into production-ready, maintainable Pro
 * Serve agents.
 * Build cross-organizational partnerships to align AI transformation with business priorities.
 * Influence senior stakeholders to secure resources and drive adoption without formal authority.
 * Measure and report business impact, including adoption, cycle time reduction, and margin improvements.
 * Continuously refine delivery methodologies using data-driven analysis and feedback.