Python Developer in London

The role involves being a core engineer on the data and intelligence layer that connects Tesco’s supply chain forecasting outputs to the people and systems that act on them. The platform sits at the intersection of data engineering, applied ML, and developer infrastructure, allowing you to work across all three and own problems end to end.

This position offers varied work: one week you might design a data API, the next improve retrieval quality in a RAG pipeline, and another work with infrastructure to get a service into production. We’re looking for someone who finds this energising rather than uncomfortable.

What you’ll work on:

• Data platform: A high-performance service that integrates multiple data sources - analytical, caching, vector, and object stores - behind a clean typed API. Supply chain data is high-volume and time-sensitive; getting the data layer right underpins everything else the platform does.
• Intelligence layer: Collaborating closely with forecasting teams across the business to produce demand signals, predictions, and recommendations. The goal is to make that intelligence accessible, actionable, and explainable through well-designed APIs, ensuring the right data reaches the right place at the right time.
• LLM integration: Developing a conversational and tool-calling layer that provides supply chain teams with natural language access to platform data and forecasts. This includes working on retrieval quality, tool design, prompt architecture, and streaming response pipelines.

What we’re looking for:

• Takes ownership. When something is broken or missing, you fix it without waiting to be asked.
• Is comfortable with ambiguity. Not every problem will have a clear spec, and you can navigate that without needing handholding.
• Writes code that other engineers want to work with: readable, tested, with complexity in the right places.
• Has experience across backend services and data systems in production, with the scars to show for it.
• Can pick up new technology without being precious about what they already know.

Technically, you should be strong in TypeScript and Python (or willing to learn quickly), have built or operated data-intensive backend services, and possess some experience with LLM APIs or retrieval systems to be productive quickly, even if not at scale before. Kubernetes and cloud-native deployment experience is useful, as is supply chain or forecasting domain knowledge, though neither is required.

The work is meaningful: The platform influences ordering decisions across thousands of stores. When it works well, products are on shelf; when it doesn’t, they aren’t. This direct impact is something most engineering roles don’t offer.

Nice to have:

• Experience contributing to shared frontend/backend or developer platform infrastructure.
• Infrastructure as code — Helm, Kubernetes manifests, CI/CD pipeline design.
• Familiarity with supply chain, replenishment, or demand forecasting domains.