Level

DP World

Group VP – Digital Platform & Automation

AI in this role

ml-opsai-safety

JOB ACCOUNTABILITIES

Enterprise Architecture Governance & Standards

  • Define and own the enterprise architecture vision and multi-year roadmap spanning systems, data, and security across all domains

  • Establish and maintain enterprise architecture principles, standards, and reference architectures consumed by all three domain teams

  • Chair the Logistics Architecture Review Board (LARB) — the governance forum for all significant technology decisions across Logistics 

    domains

  • Act as the final authority for major architecture decisions, trade-offs, and exceptions across the entire logistics technology estate

  • Approve or reject domain deviation requests from architectural standards; own the architecture governance cadence and approval rules

  • Define the external integration framework — how DP World Logistics platforms connect to carriers, customs systems, and trade networks

 

Platform Architecture & Integration

  • Define the platform-first strategy — identify capabilities built once and reused across all three domains to prevent fragmentation

  • Own integration architecture standards: API design principles, event-driven patterns, async messaging, and data exchange protocols

  • Maintain living reference architectures: microservices patterns, deployment topologies, scalability playbooks, and resilience patterns

  • Own cloud architecture strategy (GCP, Azure, AWS) — including multi-cloud standards and cloud-native platform engineering practices

  • Define Infrastructure-as-Code, CI/CD architecture expectations, container orchestration standards, and observability frameworks

  • Track and drive remediation of platform-level technical debt across all three domains through a consolidated roadmap

 

Logistics Data Strategy & Data Architecture

  • Own the Logistics Data Strategy — define the vision, architectural approach, and roadmap for how data flows across the logistics technology estate

  • Define the data architecture: data mesh patterns, domain data ownership boundaries, and shared data platform approach

  • Establish data governance standards: master data management, data quality frameworks, data lineage, and metadata management

  • Define streaming and batch data architecture — event sourcing, change data capture, and real-time analytics pipeline patterns

  • Architect the AI/ML platform: model serving infrastructure, ML Operations (MLOps) patterns, and responsible AI governance guardrails

 

Logistics Information Security Architecture

  • Own the Logistics Information Security architecture standards and reference patterns applied across all logistics domain 

    and platform systems

  • Define and enforce zero-trust network architecture, identity and access management (IAM), and privileged access management (PAM)

  • Own cloud security architecture: landing zone design, Cloud Security Posture Management, and workload security standards

  • Define application security architecture standards: secure SDLC, threat modelling, API security, and secrets management

  • Lead security architecture reviews at LARB; partner with CISO on compliance architecture (SOC2, ISO27001, GDPR)

  • Align with Enterprise Information security standards 

 

Logistics Operational Automation Technology Strategy

  • Own the Logistics Operational Automation Technology Strategy covering Robotic Process Automation (RPA), AI-driven workflows, and intelligent process automation

  • Define reference architectures for RPA deployments, AI-driven workflow orchestration, and human-in-the-loop automation patterns

  • Evaluate and standardize the automation technology stack — RPA platforms, AI/ML workflow engines, and process mining tooling

  • Identify high-value automation opportunities across all three domains in partnership with Domain SVPs and VP Product COE

  • Own the integration architecture between automation systems and core logistics platforms; govern automation decisions at LARB

 

Architecture Team & Domain Architect Leadership

  • Build and lead a high-performing central architecture team: Principal Architects covering Platform, Data, Security, and Operational Automation

  • Own the dotted-line governance relationship with domain architects embedded in each of the domain SVP organizations

  • Run the architectural community of practice: standards reviews, architectural patterns library, and cross-domain architectural learning

  • Coach domain architects to raise architectural quality across the organization — not just govern from a central function

  • Act as senior technical advisor to Domain SVPs and the Logistics EVP on complex architectural trade-offs and investment decisions

  • Represent DP World Logistics Technology with cloud providers, strategic technology vendors, and external architecture forums
     

 

QUALIFICATIONS, EXPERIENCE AND SKILLS

 

Qualifications

  • Bachelor’s degree in computer science, Software Engineering, or related technical discipline

  • Master’s degree in computer science (preferred)

 

Experience

  • 24+ years in technology, with 10+ years in senior enterprise or solutions architecture roles across complex, multi-domain environments

  • Proven experience defining and governing enterprise architecture strategy across multi-domain or multi-product technology organizations

  • Track record of leading architecture governance at scale — architecture review boards, standards bodies, or equivalent governance function

  • Demonstrated experience building and leading high-performing architecture teams including principal-level architects

  • Experience in logistics, supply chain, trade finance, or freight technology strongly preferred

  • Hands-on experience in data architecture, AI/ML platform architecture, and operational automation at enterprise scale

 

 

#LI-VG1

 

How we rate this

Group VP – Digital Platform & Automation at DP World rates 72 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsAI Safety

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. How do you think about the risk of an AI system in this kind of role failing silently?
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

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  • List these exact terms on your resume: ML Ops and AI Safety. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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