Principal AI Engineer

Data AI/ML (Artificial Intelligence and Machine Learning) Engineering involves the use of algorithms and statistical models to enable systems to analyze data, learn patterns, and make data-driven predictions or decisions without explicit human programming. AI/ML applications leverage vast amounts of data to identify insights, automate processes, and solve complex problems across a wide range of fields, including healthcare, finance, e-commerce, and more. AI/ML processes transform raw data into actionable intelligence, enabling automation, predictive analytics, and intelligent solutions. Data AI/ML combines advanced statistical modeling, computational power, and data engineering to build intelligent systems that can learn, adapt, and automate decisions.

Principal AI Engineer AI, Optimisation Intelligence and Agent Orchestration

We are building an AI-powered operating model for Ocean Operations and a next-generation optimisation capability for global Network Design. This role is not limited to agent orchestration or execution workflows. It is a senior technical leadership role for how AI strengthens optimisation methods, modelling, and decision quality across both planning and execution. The remit is broader than a standalone AI feature set. It covers how AI, optimisation, and engineering come together to deliver better network decisions at scale, while also shaping agentic decision systems in Control Tower style execution environments.

The Principal AI Engineer will set the technical direction for AI-augmented optimisation and intelligent operational decisioning. This person will lead through specialists in optimisation, modelling, heuristics, analytics, and experimentation. They will define where AI can materially improve search, structural recommendations, and solver-backed workflows, while also guiding the design of multi-agent systems for reasoning, orchestration, exception handling, and human-in-the-loop execution.

We are looking for a senior technical leader with deep credibility across both AI and optimisation, and with the ability to lead through highly skilled specialists rather than doing all modelling work personally. The strongest profile will combine experience in agentic AI systems and human-in-the-loop workflows with strong grounding in optimisation methods such as heuristics, search, mathematical programming, decomposition, or hybrid AI plus OR approaches. This person should also be comfortable directing teams working on modelling, experimentation, performance improvement, and implementation into production environments.

This role is expected to lead through others. The Principal AI Engineer should create the technical direction, decision framework, and quality standards for a broader team of optimisation, analytics, and AI specialists. The role should not be framed as a lone architect writing models end to end. It should be framed as the senior leader who sets the optimisation intelligence agenda and ensures that specialist work compounds into a coherent capability.