Amazon's Global Procurement Organization (GPO) sources products and services, empowering Amazon worldwide operations to fulfill their customer promise. Within GPO, Sourcing Excellence (SE) enables core procurement capabilities, and drives cost innovation and digital transformation.
We are seeking a strategic, hands-on leader to own GPO's AI-powered Market Intelligence, Digital Cost Solutions, and Data Management capability under Sourcing Excellence team. This role leads a team responsible for transforming Market Intelligence into an AI-powered self-serve intelligence layer serving all GPO Category teams globally — while driving cost analytics, directly supporting Should-Costing project delivery and enabling Value Engineering workflows.
The role combines four capability streams:
- AI-Powered Market Intelligence — Governing and orchestrating a wide range of specialist MI agents (Construction, Packaging, Equipment, MHE, Services, Geopolitical Risk, Renewable Energy)
- Digital Cost Solutions and Analytics — Building bespoke AI tools, dashboards, and automation for Sourcing Excellence workflows
- Knowledge Hub & Datalake — Owning the SE core data infrastructure that underpins cost modelling, benchmarking, and intelligence across the organization
- Should-Costing & Value Engineering (VE) Support — Directly delivering should-costing projects alongside Cost Engineering and feeding cost improvement catalogues and data into VE workflows
Key job responsibilities AI & Digital Solutions Strategy
Define and execute the MI agent roadmap across all L1 categories
Establish AI governance: accuracy, freshness, feedback loops, and cost-to-serve
Drive self-serve adoption KPIs and scale the tool ecosystem
Own the intelligence data supply chain — vetting, contracting, and maintaining 3P/public sources; defining the category-level source of truth Team & Stakeholder Leadership
Lead and develop a team of AI & MI Solutions Specialists
Create a high-performance team culture balancing innovation velocity with operational rigor
Serve as the intelligence partner to Category Managers, Cost Engineering, and cross-functional teams (Finance, Engineering, Operations)
Manage external 3P data provider and technology partner relationships Market Intelligence Integration with Cost & Value Engineering
Structure market data, benchmarks, and cost indices for ingestion into should-cost models and value engineering workflows
Own the Sourcing Excellence Knowledge Hub and core data-lake — data taxonomy, quality standards, access governance
Ensure knowledge assets are discoverable, current, and structured for both human use and AI agent ingestion
Directly support and deliver should-costing projects alongside the Cost Engineering team — building bottom-up cost models, validating cost drivers, establishing should-cost targets
Basic Qualifications
- Experience in program or project management
- Experience implementing repeatable processes and driving automation or standardization
- Experience owning program strategy, end to end delivery, and communicating results to senior leadership
- Bachelor's degree in supply chain management, operations, engineering, analytics or related field
- Experience deploying AI/ML or advanced analytics in a business context
- Track record transforming manual processes into self-serve/automated models
- Relevant strategic sourcing and category management in indirect categories such as professional services, support or maintenance spend, supply chain, forecasting, manufacturing, sourcing/procurement, or vendor management experience
Preferred Qualifications
- Master's degree, or MBA in business, operations, human resources, adult education, organizational development, instructional design or related field
- Experience being responsible/leading large and complex negotiations
- AI&Automation: Experience in leveraging AI, machine learning, or advanced analytics to improve cost modeling, automate procurement workflows, or build scalable datasets.
- You don't need to be a data scientist but you should be comfortable working alongside AI teams, curating training data from real-world projects, validating model outputs, and identifying where intelligent automation can multiply your impact. A track record of enabling (not just consuming) AI tools in a procurement or engineering context is a strong differentiator.
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