IODT Solution Delivery Leader

Qnity Electronics, Inc.; Wilmington (DE); Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Hybrid work model

Competitive compensation and benefits

Accessibility support

Job summary

Qnity Electronics, Inc. 正在寻找一位在数字化制造与 MES 领域具备丰富经验的高级经理，负责全球 MES 策略、架构与落地。您将主导跨区域的多厂商项目，推动 AI 在制造运营中的落地应用，并推动数据驱动的智能制造转型。

该职位需要在混合工作环境中与全球团队协作，全面负责MES相关的供应商、数据、平台与流程整合，推动 OT 安全、合规及高效运营，直接向执行团队汇报并引领跨职能变革。应具备扎实的行业知识与出色的沟通能力。

Qualifications

• 在制造 IT/OT 领域有 10 多年的经验，具备在半导体、电子等复杂行业交付 MES 的能力。
• 具备全球范围内团队与多厂商项目的领导与协作经验。
• 熟悉 COTS/自研/遗留系统的混合架构与过渡路线。
• 具备将 AI/ML/生成式 AI 引入制造运营的能力与经验。

Responsibilities

• 定义并推进多年的 MES 战略及参考架构，支持 Industry 4.0 与数字线索。
• 搭建可组合的 MES 架构，权衡 COTS、定制与配置的取舍。
• 主导端到端交付（发现阶段 → 高稳定性运行阶段），采用 DevOps 与产品团队运作模式。
• 与制造、质量、供应链、IT/OT 安全等部门协作，向高管汇报价值并推动变革管理。

Skills

制造 IT/OT 经验

MES 实施/现代化

全球团队领导

多厂商项目管理

ISA-95 知识

MES 平台经验

AI/ML 在制造业应用

敏捷/SAFe 领导力

高管沟通能力

Education

计算机科学或工程本科学历

硕士或 MBA 优先

Tools

Critical Manufacturing

AVEVA

TrackSys

Rockwell FactoryTalk

GE Proficy

iBASEt

Tulip

Power Automate

Visio

Job description

您是否渴望助力激动人心的先进电子领域的下一次飞跃？您是否希望跟我们一起解决难题， 共同推动电子技术和互联科技的快速发展？那么，带着您的解决问题的能力、热情和创造力，与我们一起推动电子领域的下一次飞跃。

在启诺迪，我们不仅是先进电子和高科技领域材料及解决方案的全球领导者，更是一个紧密团结、充满激情、勇于挑战的团队。我们所有敬业的团队都致力于将尖端技术变为现实。我们重视具有前瞻性思维的挑战者、突破界限的开拓者以及各个部门的多元化视角，因为我们深知，我们在推动世界进步、造福全人类方面扮演着至关重要的角色。了解如何加入我们，开启或加速您的职业生涯。

Senior Manager, Digital Manufacturing Systems (MES, AI & Industry 4.0)

Function: Integrated Operations & Technology – Digital Technology |

Location: [Wilmington, Cheonan, Hsinchu, etc.] / Hybrid (20–30% travel) | Scope: Global, multi-site, multi-vendor

Role Summary

Global leader responsible for MES, smart manufacturing, digital factory transformation, and AI-enabled manufacturing operations. Define and execute the enterprise MES strategy across our global manufacturing network. Own the vision, architecture, roadmap, and end-to-end delivery of modern MES capabilities in a deliberately hybrid landscape — where COTS, custom-built, and legacy systems each play a role chosen on the merits of the problem. Champion a fit-for-purpose philosophy: leverage COTS where it accelerates time-to-value, and invest in custom or in-house solutions where differentiated process know-how, speed of iteration, or unique manufacturing physics demand it. Enable manufacturing operations with AI by embedding intelligence into MES workflows, decisions, and the operator experience.

Key Responsibilities

Strategy & Architecture

• Define and evolve the multi-year MES strategy and ISA-95-aligned reference architecture supporting Industry 4.0 and the digital-thread vision.
• Establish a fit-for-purpose sourcing framework guiding COTS-vs-custom-vs-configure decisions case by case — weighing differentiation, TCO, change agility, supplier viability, and the value of internal IP.
• Preserve and modernize strategic in-house assets that encode proprietary process expertise; pursue standardization where it pays (data models, integration contracts, identity, observability, security, DevOps) without forcing convergence onto a single MES product.
• Architect for composable MES: stable cores plus best-fit specialized modules and custom extensions.

Solution Delivery

• Own end-to-end delivery (discovery → hypercare → run & maintain) using DevOps and product-team operating models, with distinct playbooks for COTS, custom builds, and legacy modernization (strangler-fig).
• Manage scope, schedule, budget, risk, and benefits realization across concurrent global rollouts; establish engineering standards, DevOps/CI-CD, and OT-grade change control for both COTS configuration and custom code.

AI Enablement of Manufacturing Operations

• Define and execute the AI-for-Manufacturing roadmap integrated with MES — yield, throughput, quality, maintenance, scheduling, and energy.
• Embed AI/ML and generative-AI directly into MES workflows: intelligent dispatching, anomaly detection, virtual metrology, run-to-run control, recipe optimization, and automated root-cause analysis.
• Enable agentic and copilot experiences for operators, engineers, and supervisors; champion closed-loop AI with explainability and human-in-the-loop controls.
• Establish responsible-AI practices for the shop floor (validation, drift monitoring, change control, traceability) and ensure MES is a first-class producer/consumer of the manufacturing data fabric.

Integration, Data, Team & Stakeholders

• Architect integrations across MES ERP (SAP S/4HANA), PLM, QMS, LIMS, WMS, SCADA/DCS/PLC, Historians (PI), APC/FDC, and EDA; drive SEMI standards adoption (SECS/GEM, GEM300, EDA, E10/E30/E40/E90/E94/E142).
• Build and lead a globally distributed team (architects, engineers, BAs, product owners) and a multi-vendor ecosystem of MES vendors, SIs, AI/ML partners, and managed-service providers.
• Partner with Manufacturing, Quality, Supply Chain, IT/OT Security, and Data & AI; communicate strategy, progress, and value to executive leadership and lead change management for AI-assisted operations.
• Ensure OT cybersecurity (IEC 62443, NIST CSF, Purdue), AI governance, BCDR, and 24×7 resilience for shop-floor-critical systems.

Qualifications

Required

• 10+ years in manufacturing IT/OT with significant experience delivering MES in semiconductor, electronics, or comparably complex industries; as well as leading globally distributed teams and multi-vendor programs.
• Track record deploying or modernizing MES at multiple sites — combining COTS implementations with custom or in-house engineering, including at least one greenfield and one legacy-modernization effort.
• Hands-on experience with leading MES platforms (e.g., Critical Manufacturing, AVEVA, TrackSys, Rockwell FactoryTalk, GE Proficy, iBASEt, Tulip) and with custom-application (Microsoft Power Automate, Visio, microservices, event-driven, modern web/UX).
• Tangible experience bringing AI/ML or GenAI into manufacturing operations beyond pilots; familiarity with MLOps, agentic workflows, RAG, and human-in-the-loop design.
• ISA-95 / ISA-88 knowledge; SECS/GEM, OPC UA, APC/FDC, R2R, recipe management, dispatching/RTD, and genealogy/traceability; SAP integration patterns; modern cloud (Azure / AWS / GCP), containers, Kafka, MQTT Sparkplug B.
• Proven Agile/SAFe leadership at scale; strong commercial acumen (RFx, contracts, vendor governance, build-vs-buy analysis); excellent executive communication.
• Bachelor's in Computer Science or Engineering discipline required; Master's or MBA preferred.
• Fluent English required.

Preferred

• Direct experience with semiconductor, advanced packaging, or specialty-materials flows; PMP / SAFe / TOGAF / ISA-95 / ISA/IEC 62443 certifications; AI/ML or cloud-AI certifications.
• Operator copilots or agentic-AI assistants in production; digital-thread / digital-twin programs; low-code platforms (Tulip, Mendix); GxP / ISO 9001 / IATF 16949 / AS9100 environments; participation in SEMI, MESA, or OPC Foundation.

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