Manufacturing Engineering, AI Enablement Lead

What if the work you did every day could impact the lives of people you know? Or all of humanity?

At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients.

Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible.

The Manufacturing Engineering AI Enablement Lead sits at the forefront of Illumina’s AI transformation—driving the adoption, scale, and real‑world impact of AI and intelligent automation across Instrument and Consumables Manufacturing within our life sciences business. In this highly visible role, you will help translate cutting‑edge AI innovation into everyday operational advantage, enabling teams to understand what’s possible, generate high‑value demand, and deliver prioritized solutions that matter.

You will serve as a catalyst for change—championing training, enablement, and adoption so AI becomes seamlessly embedded in how work gets done. Blending strong business influence, operational expertise, and AI fluency with a solid technical foundation, you will partner closely with AI and automation developers to bring to Life Generative AI applications, intelligent workflows, agentic AI, and automation services. This is a unique opportunity to shape how AI scales across manufacturing at a company whose work advances human health globally.

Position Responsibilities:

AI Demand Generation & Business Partnership

• Partner with manufacturing sites and value streams to identify high‑value AI and automation opportunities and shape an actionable demand pipeline.

• Facilitate discovery sessions, process reviews, and value assessments to align opportunities with operational priorities.

• Translate operational challenges into well‑defined AI and automation use cases, solution concepts, and ROI projections.

AI & Automation Delivery Leadership

• Partner with IT and business stakeholders to execute RPA, Generative AI, and Agentic AI solutions.

• Lead intake, scoping, sprint planning, and delivery to ensure solutions are scalable, maintainable, and aligned with enterprise AI governance and emerging AI CoE practices.

• Collaborate closely with IT Automation & AI teams and platform owners to ensure technology readiness, security, and compliance.

• Assess and drive adoption of AI capabilities integrated with SAP EAM, Industry 4.0, Digital Twin, and other OT and manufacturing technologies.

AI Enablement, Adoption & Training

• Design and deploy comprehensive training programs to accelerate AI literacy and adoption across manufacturing operations.

• Develop enablement assets including playbooks, FAQs, demos, usage guidelines, and citizen‑developer guardrails.

• Establish feedback loops to continuously improve training, tooling, and solution usability across functions.

• Upskill manufacturing teams to effectively leverage AI in their day‑to‑day work.

Change Management & Value Realization

• Drive change‑management strategies that support new AI solutions, ensuring strong stakeholder engagement, communication, and user readiness.

• Track adoption and performance metrics, measure business impact, and report value realization to senior leadership.

• Support cultural transformation toward data‑driven, AI‑enabled manufacturing operations.

Strategic Contributions to Global Operations AI Vision

• Contribute to Global Operations’ AI roadmap, aligning AI capabilities with long‑term operational excellence and innovation goals.

• Stay current on AI, LLM, and automation trends and apply insights to guide technology evolution and solution design.

• Serve as a visible champion for responsible, secure, and value‑driven AI adoption across the enterprise.

The listed responsibilities are essential but not exhaustive and may evolve to meet business needs.

Experience & Education:

• Typically requires 12+ years of related experience with a Bachelor’s degree; or 10+ years with a Master’s degree; or a PhD with 8+ years of experience; or equivalent practical experience.

Required Qualifications:

• 10+ years of experience in