Roles & Responsibilities

The AI & Innovation Lab requires a Senior AI Forward Deployed Engineer to embed directly with operational teams across terminal operations, gate and yard planning, trade documentation, logistics and economic zones. The resource will scope, build and deploy production AI solutions against live operational problems and lead cross-functional delivery squads drawn from the business and IT without formal authority.

The role will take LLM, RAG and agentic AI solutions from prototype to embedded production, including security review, data-governance alignment and operational handover. The resource will build reusable production accelerators, prompt and agent templates, reference architectures, and internal libraries to reduce delivery time for subsequent AI projects.

The position will also establish the Lab’s MLOps/AIOps foundation, including CI/CD for models and agents, model registries, evaluation pipelines, monitoring, versioning and deployment standards. The engineer will define engineering standards, responsible-AI guardrails and repeatable delivery playbooks that can be adopted across the wider organization.

This role is required to deliver live AI systems within port, zone and logistics operations; improve AI quality through automated and human evaluation; and optimize production AI performance, latency and operating cost. The requirement supports DP World’s direction toward reusable, scalable and value-driven AI capabilities, with regional delivery aligned to enterprise governance and standards.

Roles & Responsibilities

The AI & Innovation Lab requires a Senior AI Forward Deployed Engineer to embed directly with operational teams across terminal operations, gate and yard planning, trade documentation, logistics and economic zones. The resource will scope, build and deploy production AI solutions against live operational problems and lead cross-functional delivery squads drawn from the business and IT without formal authority.

The role will take LLM, RAG and agentic AI solutions from prototype to embedded production, including security review, data-governance alignment and operational handover. The resource will build reusable production accelerators, prompt and agent templates, reference architectures, and internal libraries to reduce delivery time for subsequent AI projects.

The position will also establish the Lab’s MLOps/AIOps foundation, including CI/CD for models and agents, model registries, evaluation pipelines, monitoring, versioning and deployment standards. The engineer will define engineering standards, responsible-AI guardrails and repeatable delivery playbooks that can be adopted across the wider organization.

This role is required to deliver live AI systems within port, zone and logistics operations; improve AI quality through automated and human evaluation; and optimize production AI performance, latency and operating cost. The requirement supports DP World’s direction toward reusable, scalable and value-driven AI capabilities, with regional delivery aligned to enterprise governance and standards.