About The Position

Customs Support Group (CSG) is the European market leader in customs services, operating across 15 countries. CSG is owned by private equity and is a fast-growing, dynamic, data-driven company dedicated to expanding its presence through strong organic growth and strategic acquisitions. Its key priorities include digital transformation, operational excellence, and customer experience, all aimed at driving growth and enhancing efficiency. In this role, you will take our AI stack and lead its development and customization for the market. This is a builder and do-er role. You will design, test, and implement practical and compliant agentic AI solutions on top of foundation models for document understanding, classification support, retrieval over our own procedures and tariff material, and agents that carry multi-step operational work end to end. You are not being asked to train models from scratch, but to make existing models behave reliably enough that operations staff trust them with customs declarations, where being wrong has consequences. Working closely with Operations, Transformation, IT, and Group teams, you will turn business needs into scalable solutions.

Requirements

  • 1-2 years AI engineering, software engineering, or intelligent automation, including LLM or AI features that real users depended on.
  • Strong Python and SQL, with production code ownership. Not familiarity.
  • Demonstrable experience integrating large language models into production systems — prompt and context design, retrieval-augmented generation, structured output, and handling failure gracefully.
  • Practical experience with at least one major cloud AI platform (Azure AI, AWS Bedrock, or Google Vertex).
  • Solid full stack backend engineering fundamentals — APIs, data pipelines, testing, CI/CD.
  • Strong communication skills — you will spend real time with operations staff who are experts in customs and not in AI.
  • Professional fluency in English.

Nice To Haves

  • Evaluation engineering: building eval harnesses and regression suites for non-deterministic systems, LLM-as-judge approaches, and human-in-the-loop review design. This is the single strongest signal we look for and we will weight it heavily.
  • Context engineering: designing and version-controlling what a model sees — retrieval strategy, memory, tool descriptions, and policy layers that constrain what an agent is allowed to do.
  • Agent orchestration frameworks and standards (LangGraph, MCP, Temporal or equivalent), and experience with long-running or multi-step agent workflows.
  • Observability and cost control for inference at volume.

Responsibilities

  • Develop and customize AI solutions for the market, from prototype through to production ownership.
  • Be curious and prepared to self-learn to use generative-AI to build agents that make a difference to our business.
  • Identify automation and decision-support opportunities across customs and business processes, and size them honestly before building.
  • Design solutions using generative AI and large language models — retrieval, tool calling, structured extraction from customs documentation, and agentic workflows where they genuinely fit.
  • Own the evaluation. Define how we know a solution is working before it ships, and how we know a change has not made it worse. This is treated as core to the role, not an afterthought.
  • Manage pilots and implementation, and set the criteria for killing a pilot as clearly as the criteria for scaling it.
  • Monitor performance, inference cost, latency, and business impact.
  • Collaborate with local teams, Group functions, and technology partners.
  • Contribute to privacy, security, and AI governance compliance, working with Group Legal and IT Security. You should understand how the EU AI Act applies to what you build, and be able to produce the documentation that goes with it.

Benefits

  • A key role in shaping AI capabilities.
  • The opportunity to build solutions with direct business impact, on real operational volume rather than pilots that never leave the lab.
  • An international and fast-evolving environment, with peers in other Customs Support Group markets working on the same problems.
  • Professional growth opportunities, including a budget for conferences, certification and model/compute costs for your own experiments.
  • Permanent role.
  • Hybrid working.
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