Engineering Manager – AI Digital Twin & Operations Research

What: Lead an engineering squad building APMT's Operations Intelligence capability. You will own delivery of AI-powered digital twins, integrated planning systems and operations research models across vessel, yard, gate and rail workflows. You will be hands-on in architecture and code reviews, grow a high-performing team, and turn the platform roadmap into production systems that move ROIC.

Why: This platform unifies vessel, gate, yard and rail operations into one coordinated system that integrates with the Future Execution Platform. It closes the loop from planning to execution. When OR models and digital twins predict bottlenecks and remove waste before it hits operations, that is competitive separation, and your squad builds it.

• Build MILP, Constraint Programming and stochastic optimization models for berth scheduling, storage allocation and equipment routing, the mathematical backbone of the AI Big Bet
• Apply optimization to historical terminal designs to accelerate new terminal planning and shorten time-to-revenue
• Use DES to model operational continuity during expansion projects, as volume grows and construction constrains space
• Ship prescriptive solvers that produce executable plans and recommendations, not just predictions

• Extend the Discrete Event Simulation engine across vessel, gate, yard and rail to predict bottlenecks and test scenarios before they reach operations
• Build self-learning optimization engines for yard strategy, decking and container positioning
• Deliver integrated planning components that adjust in real time as vessels delay, volumes surge or equipment fails
• Build decision support tools that turn complex trade-offs into clear recommendations for operations teams

• Deploy AI-powered process mining to find and remove waste from berth allocation to gate release
• Build continuous benchmarking that tests terminal performance against global best practice
• Deliver dashboards that connect frontline moves to financial outcomes
• Build predictive equipment utilization and labour optimization models so terminals serve more volume with the existing asset base

• Decompose monolithic simulation models into modular, API-accessible components that AI agents can call on demand
• Build agentic workflows that select and orchestrate simulation APIs based on operational questions, turning weeks of custom modelling into fast answers

• 10+ years in software or data engineering, including 3+ years leading engineers who ship AI/ML systems to production with measurable business impact
• Strong hands-on expertise in Python/R data science ecosystems, cloud infrastructure (AWS/Azure/GCP) and modern MLOps
• Practical experience with optimization (MILP/CP), simulation, predictive analytics or industrial IoT in logistics, manufacturing or infrastructure
• Credible enough technically to review designs, unblock engineers and make sound build decisions

• You understand how your team's work flows into ROIC through operational efficiency, commercial growth and concession wins
• You build reusable components, so each new DES or OR model strengthens the platform across the terminal network
• You translate operational realities into engineering requirements and explain technical trade-offs in terminal language

• You lead a squad of 6–10 engineers and data scientists, setting priorities, running delivery and holding a high quality bar under Engineering Excellence standards
• You coach and grow your engineers, hire well and build a team that ships, learns and improves
• You work closely with product owners, operations experts and peer squads to land integrated outcomes
• You turn a defined roadmap into crisp sprint plans and raise risks early

• Background in ports, logistics, supply chain or asset-intensive operations
• Understanding of maritime operations, terminal economics or heavy industrial optimization

Your squad's models and tools will help APMT win more business, run terminals more efficiently and compete on intelligence, not just scale. Every model you ship and every waste stream you remove flows directly to shareholder returns and better service for the supply chains.

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Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.

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