Vice President, Technology & Engineering Strategy (Intelligent Infrastructure)

At Jabil (NYSE: JBL) we are proud to be a trusted partner for the worlds top brands offering comprehensive engineering supply chain and manufacturing solutions. With 60 years of experience across industries and a vast network of over 100 sites worldwide Jabil combines global reach with local expertise to deliver both scalable and customized solutions. Our commitment extends beyond business success as we strive to build sustainable processes that minimize environmental impact and foster vibrant and diverse communities around the globe.

Summary

Executive leader responsible for defining and executing JabilsIntelligent Infrastructure (II) technology and engineering strategy driving the shift toAI-enabled platform-based engineering and infrastructure systemsacross design manufacturing and digital operations.

Owns alignment ofAI data electrical systems and engineering workflowsto deliver scalable capabilities improved productivity and differentiated customer solutions.

Core Responsibilities

1. Strategy & Roadmap

• Defineenterprise II technology strategy and 3-year roadmap
• Align engineering AI and infrastructure investments to business outcomes
• Translate market/customer needs into scalable engineering capabilities

2. Platform & Architecture Leadership

• Establishplatform-first architectureacross:
  • AI infrastructure (compute networking storage)
  • Electrical systems (power thermal rack integration)
  • Engineering toolchains (EDA PLM AI-assisted workflows)
• Definestandards reference architectures and integration models

3. AI-Enabled Engineering Transformation

• Drive adoption ofAI across engineering workflows including:
  • Design automation (schematic/PCB generation DFM validation)
  • Planning and estimation automation
  • AI-assisted validation and design reviews
• Shift engineering frommanual processes AI-augmented execution

4. Data & Digital Foundations

• Establishcore data architecture(models pipelines reporting)
• EnableAI-ready engineering data environment
• Standardize data flows across engineering manufacturing and operations

5. Governance & Investment

• Leadtechnology and architecture governance
• Drivetool rationalization and platform standardization
• Guideinvestment decisions (platforms partnerships capabilities)

6. Cross-Functional Execution

• Align Engineering Digital Ops AI PMO Supply Chain and BUs
• Lead global teams of architects engineers and technology leaders
• Ensure consistent execution across regions and programs

Specific Engineering Deliverables

A. Architecture & Platform

• EnterpriseAI Infrastructure Reference Architectures(rack compute networking power cooling)
• Standardelectrical system design frameworks(power distribution thermal signal integrity)
• Engineering platform architecture(EDA AI data integration)
• System-level block diagrams and integration modelsacross II stack

B. AI-Enabled Engineering Systems

• DeployedAI-assisted ECAD tools(schematic generation PCB layout validation DFM automation)
• AI-driven design review systems(requirements validation architecture verification)
• Engineering copilots / assist toolsintegrated into workflows
• Automatedplanning estimation and capacity models

C. Data & Digital Infrastructure

• Standardizedengineering data models(design BOM validation test)
• Scalabledata pipelines for AI training and inference
• Integratedengineering metrics and reporting platforms
• Digital backbone enablingend-to-end traceability (design build validate)

D. Engineering Process & Productivity

• Standardizeddesign workflows and toolchainsacross II
• Reduced design cycle time via:
  • Automated checks (DFM rules validation)
  • AI-assisted design iteration
• Measurable improvements in:
  • Engineering throughput
  • Planning efficiency
  • Rework reduction

E. Infrastructure Systems (Physical Deliverables)

• AI-optimizedrack-level system designs(compute storage networking)
• Integratedpower and cooling architecturesfor AI workloads
• Validatedend-to-end II solutions(design manufacturing deployment)
• Scalable system configurations forcustomer-specific AI platforms

F. Governance & Standards

• Publishedarchitecture standards and design guardrails
• Technologyselection frameworks and tool evaluation models
• DefinedAI/engineering lifecycle governance processes
• Centralizeddecision logs and architecture review outputs

Success Metrics

• % adoption ofstandardized platforms and toolchains
• Reduction inengineering cycle time and rework
• Increase inengineering capacity without headcount growth
• Scaled deployment ofAI-enabled capabilities across II
• Improvedcost performance and time-to-marketof solutions

Profile

• Bachelors degree in Engineering or related field
• 20 years in engineering systems architecture or technology leadership
• Deep expertise in:
  • Electrical systems and infrastructure (power thermal compute)
  • Engineering design ecosystems (EDA PLM validation)
  • AI-enabled systems and digital platforms
• Proven track record drivingenterprise-scale transformation

Why This Role Matters

This role is central to enabling Intelligent Infrastructure by:

• TurningAI data engineering into scalable capability
• Unlockingengineering capacity and speed at scale

Positioning Jabil at the center of theAI infrastructure ecosystem

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