Fullstack AI engineer in logistics

IFS Logistics (built and launched as 7bridges, now part of IFS) is an AI-native enterprise logistics platform. We unify transport data, optimise carrier spend, and automate execution for enterprise shippers and logistics companies. We are a small, dedicated product and engineering team inside IFS, reporting into the commercial organisation rather than central R&D. Pure SaaS, zero consultancy: if a customer needs us to operate the software for them, we have failed.

• API v3 and the service boundaries that let four product areas share one identity, permission and navigation model without a shared mess.
• SSO, tenancy and permissions done once, properly — "all data visible by default, restricted only by exception".
• A demo environment that is a real product surface, not a fixture — commercially load-bearing and used every week.
• IFS Intelligence and IFS Cloud integration, including the embedding path opened up by Project Oliver.
• Where the agent sits in each new surface, and the guardrails, observability and cost controls that make agentic behaviour safe to ship.

• Around eight years or more building and running production software, with real depth in Python/Django REST API design, data modelling and service reliability.
• You have set technical direction for a team: chosen the approach, written it down, defended it, and changed it when you were wrong.
• Strong on performance, cost and observability. You have owned the pager as well as the design doc.
• Genuinely fullstack — comfortable in React and able to raise the bar on frontend work you do not write yourself.
• You raise other people's standards. Review, pairing and honest feedback are things you do by default.
• AI-native in practice: you build with Cursor and Claude daily, you know how to give an agent the right context, and you can tell when its output is wrong.
• You form and state a view. Ambiguity is the job, not a blocker.
• Будет плюсом: Multi-tenant enterprise SaaS, SSO/identity, or ERP integration experience; LLM agent orchestration, RAG or evals in production; Shipped agents into a product for real work, like agentic audit or agent-managed fulfilment rules, with a view on where an agent earns its place and where it does not; Simulation or scenario modelling: synthetic data or replay used to prove out logic before it ships; BigQuery, dbt, Pub/Sub, GCP, Kubernetes, Terraform; Logistics, supply chain or freight

• You'll need to be based in either the UK or the Netherlands - we're a remote team with clusters of people in London and Amsterdam.
• We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging. Our commitment ensures you can work in a way that suits you best, while also engaging with colleagues to share ideas and build meaningful relationships.