AI Futures has been engaged to find a Senior AI/ML Engineer for one of the world’s largest logistics organisations - a company where AI is not a side project but the engine being rebuilt into the core of how goods move at global scale.

The company

A leading international logistics and supply chain organisation with operations spanning transport, warehousing, and last-mile delivery across dozens of markets. The AI and engineering teams are working on problems that have genuine operational consequence - route optimisation, demand forecasting, warehouse automation, and the agentic workflows that tie them together. This is not a proof-of-concept environment. It is production AI at logistics scale.

The role

You will design, build, and deploy AI and ML solutions embedded directly into logistics and supply chain operations - translating complex business processes into intelligent, production-grade systems. You will work across the full stack: from model development and agentic workflow orchestration through to enterprise integration and responsible AI governance. The expectation is that you ship things that work reliably in production, at scale, under real operational pressure.

What you’ll do

• Design and build AI-driven applications and agentic workflows that optimise logistics operations - route and network optimisation, demand forecasting, warehouse telemetry, capacity planning, and transport procurement
• Develop and deploy solutions leveraging LLMs, Generative AI, and cloud-native AI services across GCP (Vertex AI) and/or Azure (Azure OpenAI, Azure AI Document Intelligence, LangGraph)
• Build and orchestrate multi-step AI workflows using frameworks such as LangChain, ADK, or equivalent agentic engineering tooling
• Integrate AI solutions with enterprise platforms ensuring robust API design and system interoperability
• Implement human-in-the-loop controls, validation mechanisms, and escalation paths to ensure responsible and reliable AI usage in operational contexts
• Review AI-generated and human-written code for correctness, architecture quality, security, test coverage, and production readiness
• Contribute to reusable engineering standards, implementation patterns, and best practices that accelerate future delivery
• Identify and mitigate risks related to AI outputs: data privacy, bias, security, and hallucination in high-stakes logistics contexts

What you’ll bring

• Proven experience designing and deploying ML or AI systems in logistics, supply chain, or operations-intensive industries.
• Hands-on experience with Generative AI and LLMs in production: prompt engineering, RAG, unstructured data processing, and multi-step workflow orchestration
• Experience building agentic AI solutions using LangChain, LangGraph, ADK, or comparable orchestration frameworks
• Strong Python; additional comfort with TypeScript or Node.js is an advantage
• Cloud platform experience - GCP (Vertex AI, Cloud Run, BigQuery) and/or Azure (Azure OpenAI, App Services, Azure Functions, Azure AI services)
• Solid software engineering fundamentals: APIs, CI/CD, testing, observability, and security
• Ability to work autonomously across global, cross-functional teams while communicating clearly with technical and non-technical stakeholders

Desirable

• Experience with agentic AI applied specifically to transport network optimisation, last-mile delivery, or procurement automation
• Familiarity with operational AI governance - responsible AI frameworks, compliance standards, and human-in-the-loop system design
• Knowledge of digital twin concepts, warehouse telemetry, or IoT data integration in logistics environments
• Fluency in German; English is essential
• 
  

AI Futures has been engaged to find a Senior AI/ML Engineer for one of the world’s largest logistics organisations - a company where AI is not a side project but the engine being rebuilt into the core of how goods move at global scale.

The company

A leading international logistics and supply chain organisation with operations spanning transport, warehousing, and last-mile delivery across dozens of markets. The AI and engineering teams are working on problems that have genuine operational consequence - route optimisation, demand forecasting, warehouse automation, and the agentic workflows that tie them together. This is not a proof-of-concept environment. It is production AI at logistics scale.

The role

You will design, build, and deploy AI and ML solutions embedded directly into logistics and supply chain operations - translating complex business processes into intelligent, production-grade systems. You will work across the full stack: from model development and agentic workflow orchestration through to enterprise integration and responsible AI governance. The expectation is that you ship things that work reliably in production, at scale, under real operational pressure.

What you’ll do

• Design and build AI-driven applications and agentic workflows that optimise logistics operations - route and network optimisation, demand forecasting, warehouse telemetry, capacity planning, and transport procurement
• Develop and deploy solutions leveraging LLMs, Generative AI, and cloud-native AI services across GCP (Vertex AI) and/or Azure (Azure OpenAI, Azure AI Document Intelligence, LangGraph)
• Build and orchestrate multi-step AI workflows using frameworks such as LangChain, ADK, or equivalent agentic engineering tooling
• Integrate AI solutions with enterprise platforms ensuring robust API design and system interoperability
• Implement human-in-the-loop controls, validation mechanisms, and escalation paths to ensure responsible and reliable AI usage in operational contexts
• Review AI-generated and human-written code for correctness, architecture quality, security, test coverage, and production readiness
• Contribute to reusable engineering standards, implementation patterns, and best practices that accelerate future delivery
• Identify and mitigate risks related to AI outputs: data privacy, bias, security, and hallucination in high-stakes logistics contexts

What you’ll bring

• Proven experience designing and deploying ML or AI systems in logistics, supply chain, or operations-intensive industries.
• Hands-on experience with Generative AI and LLMs in production: prompt engineering, RAG, unstructured data processing, and multi-step workflow orchestration
• Experience building agentic AI solutions using LangChain, LangGraph, ADK, or comparable orchestration frameworks
• Strong Python; additional comfort with TypeScript or Node.js is an advantage
• Cloud platform experience - GCP (Vertex AI, Cloud Run, BigQuery) and/or Azure (Azure OpenAI, App Services, Azure Functions, Azure AI services)
• Solid software engineering fundamentals: APIs, CI/CD, testing, observability, and security
• Ability to work autonomously across global, cross-functional teams while communicating clearly with technical and non-technical stakeholders

Desirable

• Experience with agentic AI applied specifically to transport network optimisation, last-mile delivery, or procurement automation
• Familiarity with operational AI governance - responsible AI frameworks, compliance standards, and human-in-the-loop system design
• Knowledge of digital twin concepts, warehouse telemetry, or IoT data integration in logistics environments
• Fluency in German; English is essential
•