Job Description
Sea Logistics Agentic AI Engineer

It's more than a job

As a member of the Freight Forwarding team Kuehne+Nagel, you will play a key role in transporting goods, optimising processes, and fulfilling our customers' promises. And by transporting medicines, toys and important machine parts, you are not only delivering goods, you are making small and big moments possible for people all around the world. At Kuehne+Nagel, our contribution counts in more ways than we imagine.

 

Your Role

This role designs and deploys autonomous AI agents that can reason, plan, and execute tasks while integrating deeply with enterprise systems such as ERP, CRM, and logistics platforms. It ensures these agents operate safely and reliably through strong guardrails, monitoring, and humans in-inthe-theloop of-loop controls. The position also drives performance optimization, experimentation with new agentic use cases, and close collaboration with product, engineering, data, and business teams.

 

Your Responsibilities

  • Architect and develop AI agents capable of reasoning, multistep planning, decision-making, and autonomous task execution. Making--making, and autonomous task execution.
  • Implement agent frameworks using AutoGPT, LangChain, CrewAI, ReAct-based approaches, or custom internal architectures.
  • Enable robust tool use capabilities, including interaction with APIs, databases, enterprise systems, and external services. U-se capabilities, including interaction with APIs, databases, enterprise systems, and external services.
  • Develop modular, extensible agent components for reuse across business functions.
  • Connect AI agents to TMS, ERP, CRM, WMS, and other enterprise platforms.
  • Build integrations with APIs, data pipelines, event driven systems, and structured/unstructured data sources. -driven systems, and structured/unstructured data sources.
  • Enable agents to trigger workflows, generate reports, retrieve and process data, and execute decisions where appropriate.
  • Collaborate with platform and data engineering teams to ensure secure, scalable integrations.
  • Implement guardrails for safe decision-making, including policy constraints, validation layers, and fallback logic. Making, including policy constraints, validation layers, and fallback logic.-making, including policy constraints, validation layers, and fallback logic.
  • Establish human-in-the-loop review processes for high impact or sensitive actions in the loop of review processes for high impact or sensitive actions.-in-the-loop review processes for high-impact or sensitive actions.
  • Build monitoring, logging, and explainability mechanisms to ensure transparency and traceability.
  • Reduce risks related to hallucinations, bias, and unintended automation through rigorous testing and governance.
  • Improve agent reliability, latency, accuracy, and cost efficiency (including LLM token optimization).
  • Conduct benchmarking and scenario-based evaluations to measure agent performance in real business environments. Based evaluations to measure agent performance in real business environments.-based evaluations to measure agent performance in real business environments.
  • Tune prompts, memory systems, retrieval pipelines, and model configurations for consistent output quality.
  • Prototype and validate new agentic use cases, including:
    oAutonomous customer support agents
    oAI operations assistants
    oAutomated logistics and planning agents
    oData analysis and reporting agents
    oIntelligent process automation
  • Drive rapid experimentation cycles to identify high value opportunities for agent deployment. Value opportunities for agent deployment.-value opportunities for agent deployment.
  • Work closely with product, operations, engineering, data science, and business stakeholders to define requirements and deliver solutions.
  • Translate business needs into technical agent capabilities and system integrations.
  • Provide technical guidance on agentic architecture, best practices, and emerging technologies.

 

Your Skills and Experiences

Hard Skills

  • Preferably established skills specific to freight forwarding industry:
    oUnderstanding end-to-end-to-end freight operations (air, ocean, trucking, drayage).
    oKnowledge of INCOTERMS, HS codes, customs clearance, and compliance workflows.
    oFamiliarity with shipment lifecycle events: booking, documentation, consolidation, milestones, exceptions, POD, invoicing.
    oExperience with rate management, quoting engines, and carrier integrations.
    oUnderstanding capacity planning, routing, scheduling, and load optimization.Handson experience with TMS, WMS, ERP, CRM, and experience with TMS, WMS, ERP, CRM, and -on experience with TMS, WMS, ERP, CRM, and freight-specific platforms.
    oAPI integration skills (REST, SOAP, GraphQL) for carriers, brokers, and data providers.
    oWorking with EDI formats (EDIFACT, ANSI X12) commonly used in logistics.
  • Other hard skills that are required for the role.
  • Ability to integrate with event driven-driven systems (Kafka, Pub/Sub, MQ).
  • SQL and NoSQL database proficiency for operational data access.
  • Building agentic systems using LangChain, AutoGPT, CrewAI, ReAct, or custom frameworks.
  • Designing multistep reasoning, planning, and step reasoning, planning, and -step reasoning, planning, and tool-use workflows.
  • Retrieval of augmented-augmented generation (RAG) for operational documents and shipment data.
  • Prompt engineering and LLM orchestration for reliability and accuracy.
  • Model evaluation, finetuning, and optimization for tuning, and optimization for -tuning, and optimization for logistics-specific tasks.
  • Building workflow automations for booking, documentation, exception handling, and customer updates.
  • Experience with BPM tools (Camunda, Airflow, n8n, Zapier Enterprise, etc.).
  • Understanding robotic process automation (RPA) for repetitive tasks.
  • Ability to design decision trees, validation layers, and fallback logic.
  • Implementing guardrails for high-risk logistics risk logistics actions (e.g., customs filings, carrier bookings)-risk logistics actions (e.g., customs filings, carrier bookings).
  • Monitoring, logging, and auditability for regulated workflows.
  • Reducing bias and hallucinations in operational decision-making.-making.
  • Knowledge of data privacy and compliance requirements (GDPR, CTPAT, etc.)
  • Strong Python engineering skills (preferred for agent frameworks).
  • Experience with cloud platforms (Azure, AWS, GCP).
  • Containerization and deployment (Docker, Kubernetes).
  • CI/CD pipelines for agent updates and model deployments.

Soft Skills

  •  Operational problem solving – Ability to break down complex logistics workflows, identify bottlenecks, and translate them into agentic automation opportunities.
  • Solving – Ability to break down complex logistics workflows, identify bottlenecks, and translate them into agentic automation opportunities.-Solving – Ability to break down complex logistics workflows, identify bottlenecks, and translate them into agentic automation opportunities.
  • Cross functional communication – Comfortable working with operations, product, engineering, and customer facing teams to align requirements and constraints.
  • Functional Communication – Comfortable working with operations, product, engineering, and customer facing teams to align on requirements and constraints.-Functional Communication – Comfortable working with operations, product, engineering, and customer-facing teams to align on requirements and constraints.
  • Systems thinking – Understands how decisions ripple across different processes and customer commitments.
  • Adaptability –Ability to adjust quickly to changing priorities, exceptions, and new data is essential.
  • Stakeholder management – Skilled at gathering input, setting expectations, and ensuring buy-in from teams with different incentives.-in from teams with different incentives.
  • Attention to detail – Critical for compliance, documentation accuracy, and preventing automation errors in regulated workflows.
  • Analytical Mindset – Uses data to validate assumptions, measure agent performance, and refine workflows.
  • Proactive ownership – Takes initiative to identify automation opportunities and drive them from concept to deployment.
  • Risk awareness & judgment – Understands when automation is appropriate and when human oversight is required.

 

Good Reasons to Join

At Kuehne + Nagel, you get to grow your expertise, shape processes and deliver innovative solutions. We are continuously building our local and global network and our product portfolio, creating career opportunities in different fields of work worldwide. As a leader in the logistics industry, we provide a collaborative and IT driven environment where you will work with motivated and customer-centric colleagues across the world.

 

Who we are

Logistics shapes everyday life - from the goods we consume to the healthcare we rely on. At Kuehne+Nagel, your work goes beyond logistics; it enables both ordinary and special moments in the lives of people around the world.

As a global leader with a strong heritage and a vision to move the world forward, we offer a safe, stable environment where your career can make a real difference. Whether we help deliver life-saving medicines, develop sustainable transportation solutions or support our local communities, your career will contribute to more than you can imagine.

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