Illumina

Illumina

Supply Chain AI Enablement Lead

US - California - San Diego

H1B sponsorship available$118k-$177kDetected 30 days ago
AzureLLMsAgentic AIAgileSAPSupply ChainProcess ImprovementERPLeadershipCommunicationCollaboration

About the role

  • Supply Chain AI Enablement Lead will drive the adoption, scaling, and impact of AI and intelligent automation across Global Supply Chain.
  • This role ensures that teams understand AI capabilities, generate high‑quality demand, execute prioritized initiatives, and deliver the training and change‑management needed for sustained value realization of everyday AI.
  • This individual will combine strong business influencing ability, process expertise, and AI fluency with a solid technical background to partner with a team of AI and automation developers building solutions such as Generative AI apps, intelligent workflows, Agentic AI and automation services.

Responsibilities

  • Partner with Plan, Source, Deliver and Regional Supply Chain leaders to identify high‑value AI opportunities and shape an actionable demand pipeline.
  • Partner with IT and business organizations to execute a RPA, GenAI or Agentic AI Solutions
  • Manage intake, scoping, sprint planning, and delivery to ensure solutions are scalable, maintainable, and aligned with enterprise AI governance (aligned with emerging AI CoE practices referenced in GO & IT collaboration)
  • Partner closely with IT Automation & AI teams, and platform owners to ensure technology readiness, compliance, and security.
  • Design and deploy comprehensive training programs to accelerate AI literacy and adoption within operations
  • Build enablement assets including playbooks, FAQs, demos, guidelines, and citizen‑developer guardrails.
  • Design and deploy training for the Global Supply Chain organization to upskill the talent with AI
  • Drive change‑management plans supporting new AI solutions, ensuring strong stakeholder engagement, communication, and user readiness.
  • Support cultural transformation toward data‑driven and AI‑enabled operations.
  • Stay current on AI/LLM trends, automation platforms, and operational use cases to guide technology evolution and solution design.

Requirements

  • 8+ years of experience in Global Operations, Supply Chain, Quality, or similar environments.
  • Strong understanding of Plan, Source and Deliver business processes with strong foundation of tools like SAP, Ariba, Icertis Contract Lifecycle Management etc.
  • Strong understanding of operational processes and applied AI/Agentic AI/automation capabilities (LLMs, workflow automation, predictive models, etc.).
  • Experience with RPA, LLMs, orchestration tools, or process mining. (UiPath, Azure Open AI, Microsoft CoPilot Studio, Anthropic)
  • Experience managing global project portfolios, agile teams, and solution delivery lifecycles.
  • Hands-on experience deploying AI/automation solutions in complex operational environments.
  • Familiarity with enterprise AI governance and risk frameworks
  • Strong executive presence and ability to inspire trust across technical and business teams.
  • Ability to simplify complex AI concepts for broad audiences.
  • Typically requires 10+ years of related experience with a Bachelor's degree
  • Required
  • Demonstrated ability to influence senior stakeholders and drive cross-functional transformation.
  • Technical fluency and ability to lead teams across automation development, AI engineering, or low code/automation platforms.
  • Understanding of industry trends of.ai products can drive significant impact through augmentation of tools
  • Preferred
  • Exposure to MES, QMS, ERP, planning systems, or other operations technologies.
  • Lean, Six Sigma, or operational excellence certification.

Compensation

  • The estimated base salary range for the Supply Chain AI Enablement Lead role based in the United States of America is: $118,200 - $177,200.

Visa & Work Authorization

  • This role is not eligible for visa sponsorship.

This listing is sourced directly from Illumina's careers page and normalized into a canonical job model.