AI-Driven Manufacturing Transformation Manager

Ernst & Young Oman

Honolulu (HI)

On-site

USD 154,000 - 257,000

Full time

14 days+

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Benefits offered by this job

Medical & dental coverage

401(k) / Pension

Paid time off

Job summary

EY is seeking a Manager in our Supply Chain Manufacturing practice to lead market-facing delivery of transformation programs that blend operational improvement, digital tech, analytics, and AI. You will collaborate with client executives, engineers, quality, maintenance, IT, OT, data, and AI teams to turn priorities into scalable, measurable outcomes.

You will guide design, development, and deployment across ERP, MES/MOM, and related systems, driving value realization and continuous improvement

Qualifications

Bachelor's degree in engineering, supply chain, operations, information systems, computer science, business, or a related field.
4 to 6 years of relevant experience in digital manufacturing, manufacturing operations, supply chain, industrial technology, systems implementation, consulting, or a related environment.
Experience shaping or delivering AI, advanced analytics, or knowledge-enabled solutions within manufacturing, supply chain, engineering, quality, maintenance, or industrial operations.

Responsibilities

Lead client-facing manufacturing transformation workstreams and programs from opportunity shaping through design, implementation, deployment, and value realization.
Act as the two-way liaison between design and delivery teams by translating client needs into solution requirements and translating reusable capabilities into practical engagement plans.
Partner with the design team to prioritize solution enhancements, validate use cases, shape demonstrations, assess implementation readiness, and define documentation, training, and support for scalable delivery.
Capture lessons, recurring requirements, configuration patterns, technical constraints, and delivery feedback from engagements and incorporate them into the design backlog and solution roadmap.
Assess manufacturing processes, performance gaps, user needs, data flows, controls, and technology constraints across plant and network environments.
Translate manufacturing priorities into process designs, functional requirements, user stories, data requirements, integration requirements, acceptance criteria, deployment roadmaps, and measurable outcomes.