AI Engineer

It's more than a job

In this IT role, you will manage, develop, and support the technology infrastructure that powers Kuehne+Nagel’s global systems and operations. This contribution is vital to making both special and ordinary moments in the lives of people a reality. In fact, your work enables our teams to deliver fresh fruit, time-sensitive healthcare products and much more to people all around the world. Working in IT at Kuehne+Nagel contributes to more than we imagine.

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As an Agentic AI Engineer (m/f/d), you will be responsible for designing, building, and optimizing autonomous AI agents that improve decision-making, automate workflows, and integrate with key logistics systems across our Sea Logistics organization. You will play a key role in driving intelligent automation while ensuring that AI solutions are safe, reliable, scalable, and practical for real-world business operations.

How you create impact

• Design and develop autonomous AI agents with reasoning, planning, decision-making, and task-execution capabilities.
• Build agentic AI solutions using frameworks such as LangChain, AutoGPT, CrewAI, ReAct, or custom architectures.
• Integrate AI agents with enterprise systems, including TMS, ERP, CRM, WMS, APIs, databases, and event-driven platforms.
• Build safety and control mechanisms, including guardrails, validation layers, fallback logic, and human-in-the-loop processes.
• Develop monitoring, logging, and explainability capabilities to ensure transparency, reliability, and compliance.
• Optimize and validate agent performance for accuracy, reliability, latency, and operational cost through benchmarking and real-world scenario testing.
• Identify and prototype new agentic AI use cases across customer service, operations, planning, and reporting.
• Collaborate across teams to translate business needs into scalable technical architectures and automation solutions.

What we would like you to bring

• 3+ years of experience building agentic AI systems and integrating them with enterprise APIs, databases, and business or logistics platforms.
• Strong Python engineering skills and experience working with at least one major cloud platform, such as AWS, Azure, or GCP.
• Strong understanding of modern AI technologies, including RAG pipelines, prompt engineering, model tuning, and LLM orchestration.
• Experience with AI workflow automation and risk management, including guardrails, validation layers, fallback mechanisms, and other safety controls.
• Familiarity with modern software architectures, including event-driven systems, SQL/NoSQL databases, APIs, and distributed applications.