Software Engineer (Data & AIML)

About Maersk

Maersk is building the next generation of digital capabilities for the global supply chain.

We are re-architecting our platform with a data-first approach building a trusted scalable and reusable data foundation for current and future supply-chain use cases.

On top of this foundation we will build ML models intelligence recommendations GenAI and agentic AI to help customers and teams make better and faster decisions.

A key part of this vision is data democratization making trusted and contextualised data easy to discover understand and use across teams products models and AI agents.

About the Role

We are looking for an experienced Data AI/ML GenAI & Agentic AI Engineer to help design and build this platform from the ground up.

This role combines data engineering software engineering AI/ML and architecture. You will build reusable platform capabilities rather than one-off solutions and work closely with engineers data scientists architects product teams and supply-chain experts.

What You Will Do

Design and build scalable data and AI architecture for data-intensive systems.

Build trusted data foundations and reusable data products from multiple sources.

Build reliable batch streaming and near-real-time data pipelines based on business needs.

Enable data democratization and self-service access to trusted data.

Build capabilities for data quality governance lineage metadata security and observability.

Establish common business context and semantics so data can be effectively used by applications ML models GenAI and AI agents.

Develop and productionise ML solutions for prediction forecasting risk anomaly detection recommendations and optimisation

Build production-grade GenAI/LLM solutions using approaches such as RAG embeddings vector search and tool calling.

Build agentic AI solutions that can reason over trusted data use tools and APIs provide recommendations and take actions.

Design appropriate guardrails access controls monitoring and human oversight for AI and agentic solutions.

Build reusable APIs services and workflows that connect data applications and AI capabilities.

Use platforms such as Pipedream or similar workflow tools where they add value.

Make architecture and technology decisions considering scalability reliability security performance and cost.

Establish strong engineering practices including testing CI/CD and observability.

Contribute to architecture reviews technical design and code reviews. Mentor engineers and help establish engineering and architecture standards

About You

We are looking for someone with strong engineering data and AI fundamentals who can build production-ready systems.

You should have:

4 years of experience in software engineering data engineering AI/ML engineering or a related field.

Experience designing and building scalable distributed and data-intensive systems.

Experience contributing to or owning architecture and technical design for data or AI platforms.

Strong programming skills in Java and Python. Experience with Scala Kotlin or similar languages is a plus.

Strong understanding of data architecture data modelling distributed systems and data processing.

Experience building data pipelines data products or data platforms at scale. Experience with technologies such as Kafka Spark Databricks Flink or equivalent.

Experience with relational and/or NoSQL databases

Good understanding of data quality governance metadata lineage and observability.

Hands-on experience taking ML models from development to production including deployment monitoring and evaluation.

Experience with GenAI/LLMs and building practical production-ready applications.

Understanding of RAG embeddings vector search tool calling and LLM evaluation.

Experience or strong exposure to AI agents and agentic workflows.

Understanding of AI security guardrails access control and human oversight.

Experience with at least one cloud platform such as Azure AWS or Google Cloud.

Strong software engineering practices including automated testing CI/CD and production operations.

Strong communication and problem-solving skills. A platform mindset focused on building reusable capabilities rather than oneoff solutions.

Good to Have

Experience in logistics shipping transportation or supply chain.

Experience with real-time and event-driven architectures.

Experience with MLOps and model monitoring.

Experience with production RAG AI agents or agent orchestration.

Experience with MCP or similar agent/tool integration patterns.

Experience with knowledge graphs semantic models or entity resolution.

Experience with Pipedream or similar workflow/integration platforms.

Experience with Docker Kubernetes and cloud-native architectures.

Experience leading technical design or architecture for large-scale platforms.

Why This Role

This is a greenfield opportunity to help build the foundation for the next generation of supply-chain intelligence at Maersk. Our vision is: Data Foundation Data Products & Context ML & Intelligence Recommendations GenAI Agentic AI The data foundation is the core layer providing trusted reusable and contextualised data to products ML models GenAI applications and AI agents.

The goal is to build a platform where new data and AI capabilities can be developed faster reused across multiple use cases and scaled across the supply chain without repeatedly rebuilding the underlying foundation. You will help shape the architecture data foundation engineering practices and AI capabilities that will enable future digital supply-chain experiences at Maersk.

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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