The Opportunity

Global logistics is undergoing one of the largest technology-driven transformations of any industry. Over 90% of global trade moves through complex, interconnected supply chains spanning oceans, ports, terminals, warehouses, customs systems, and partner networks. The data generated by this ecosystem is massive, continuous, and operationally critical, yet historically fragmented and underutilized.

Maersk operates at the center of this system. Across vessels, terminals, inland logistics, and digital services, Maersk manages millions of container movements every year across more than 130 countries. Every delay, handoff, and exception generates data that directly impacts cost, customer experience, sustainability, and global commerce.

MIDAS is Maersk's integrated Data and AI platform built to turn this complexity into an advantage.

MIDAS is designed to unify data foundations and AI enablement into a single, coherent platform that supports analytics, machine learning, and generative AI at global scale. The focus is not hindsight reporting, but real-time visibility, predictive decision-making, and AI-assisted automation across the end-to-end supply chain. This includes use cases such as vessel ETA prediction, exception handling, sustainability and carbon reporting, and AI-assisted planning and operations.

This role sits at the heart of that transformation.

As a Lead Engineer in MIDAS, your work directly influences how data is trusted, how AI systems are deployed, and how decisions are made across one of the world's largest logistics networks. You are not optimizing a single product surface or internal tool. You are helping build the foundations that allow data and AI systems to operate reliably in environments where scale is non-negotiable, errors are expensive, and minutes matter.

The Role

We are looking for a Lead Engineer Data & AI Platform who brings deep technical expertise, strong engineering judgment, and hands-on experience building both data platforms and AI-enabled systems.

This is not a pure individual contributor role and not a people management role. It is a senior engineering leadership position where impact comes from technical credibility, architectural influence, and the ability to guide teams through complex decisions.

You will operate across data and AI concerns, helping teams build systems that are reliable, observable, and designed for long-term scale.

What You'll Do

You will provide senior technical leadership across teams building the MIDAS data and AI platform.

On the data side, you will guide the design and evolution of ingestion, processing, and serving layers supporting both batch and streaming workloads. You will help teams make informed decisions around data modeling, schema evolution, performance tuning, and cost efficiency in large-scale distributed systems.

On the AI side, you will enable production-grade machine learning and generative AI workloads. This includes guiding how data foundations support feature pipelines, model training and evaluation, retrieval-augmented systems, and inference services. Your focus will be on making AI systems reliable, observable, and sustainable beyond experimentation.

You will influence architecture through design reviews, reference patterns, and technical guidance rather than direct ownership of a single system. You will mentor senior engineers, challenge assumptions, and help teams converge on solutions that scale technically and organizationally.

You will collaborate closely with engineering managers, product owners, platform teams, and security stakeholders to translate platform strategy into execution.

This is a hands-on leadership role. While you may not write production code every day, you are expected to deeply understand the systems being built, engage in technical problem-solving, and bring clarity during incidents and complex design discussions.

Technical Scope

The MIDAS platform spans a broad and interconnected technical surface area. As a Lead Engineer, you will work across and influence systems involving:

Distributed data processing across batch and streaming workloads
Event-driven architectures with strong guarantees around correctness and latency
Modern lakehouse patterns using columnar storage and transactional data layers
Metadata, lineage, governance, and data quality as first-class platform capabilities
Machine learning and generative AI enablement, including feature pipelines, evaluation workflows, vector-based retrieval, and inference services
Cloud-native infrastructure with strong emphasis on automation, observability, security, and cost discipline

Strong proficiency with AWS is required. You should be comfortable designing and reasoning about systems built on services such as S3, Glue, EMR, Athena, Lambda, and related components, and understand how they behave under scale, load, and failure.

What We're Looking For

We're looking for a highly qualified engineer with deep expertise in data platforms and hands-on experience as an AI practitioner, who is ready to operate as a senior technical leader.

You bring strong fundamentals in distributed systems and data engineering. You have designed, built, and operated large-scale data platforms in production environments and understand the realities of reliability, performance, schema evolution, and cost management.

You also have real experience working with AI systems in production. This may include building or supporting machine learning pipelines, deploying models, integrating LLMs into applications, implementing retrieval-augmented systems, or setting up evaluation and monitoring for AI behavior. You understand the full lifecycle of AI systems and how deeply they depend on data quality, feedback loops, and operational guardrails.

You are fluent in Python and SQL and comfortable working with Spark or similar distributed processing engines. You are familiar with modern engineering practices such as CI/CD, infrastructure as code, and containerized execution environments. Experience with Kubernetes-based platforms and managed data or ML services is a strong advantage.

From a leadership perspective, you lead through expertise and judgment. You communicate clearly, write solid design documentation, and are trusted to make sound decisions in ambiguous situations. You influence outcomes across teams by raising the engineering bar rather than enforcing authority.

This role is well suited for an engineer who is already operating at Lead level and is on a clear trajectory toward broader senior technical leadership roles over time.

Impact and Growth

The impact of this role is significant and visible.

Your guidance will shape how data and AI systems are built and operated across Maersk's global logistics network. The platforms you influence will support critical business operations, decision-making, and sustainability initiatives across 130+ countries.

This role offers long-term growth into more senior technical leadership positions. Success here means influencing platform standards, mentoring senior engineers, and shaping architectural decisions that extend well beyond a single team or project.

If you are motivated by building durable systems, enabling others to move fast safely, and applying AI in ways that genuinely matter in the physical world, MIDAS offers a rare and meaningful opportunity.

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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