Senior Backend Engineer

About the role

A warehouse is a physical system before it is a dataset. Racks have load limits, locations have shapes, pickers walk real distances, and one site can produce hundreds of millions of events a year. As Senior Backend Engineer at WareBee you will model that complexity in code, turn it into data the product can trust, and make it answer questions in seconds.

WareBee runs on two engines. Physical AI is a living spatial model of the warehouse floor, its racks, aisles and movement. Process AI learns how work actually flows through it. You will own what keeps both fed, fast and reliable: ingestion, the data model, APIs, analytical storage, background work, and the observability that lets a small team run it with confidence at 3 am.

The problems

• Modelling a complex physical system in code: geometry, capacity, weight, units of measure, access rules, and the constraints real operations break every day
• Turning messy customer exports into clean, versioned data at scale without losing a row
• Serving interactive analytics over billions of rows, with an answer in seconds rather than a report tomorrow
• Feeding and scaling optimisation for problems that are NP-hard in the textbook sense, such as slotting, routing, batching and scheduling, where a good answer within a time budget beats a perfect one that never arrives
• Connecting racks, SKUs, orders, people and events into one knowledge graph, so the product and its AI can reason across the whole operation
• Making large, complicated data simple for customers: the right aggregate, the right default, the one number that matters

What you will do

• Design data models and APIs that are obvious to the next person who touches them
• Shape the warehouse ontology: the entities, relationships and rules that describe how a site is built and how work moves through it
• Integrate AI and ML models into production services, with clear inputs, evaluation, and a way to roll back when a model gets it wrong
• Build ingestion and processing pipelines for large warehouse datasets that recover from failure instead of losing work
• Write and tune analytical SQL on columnar and serverless engines, and know when to pre-compute and when to query live
• Work with optimisation teammates to turn algorithms into production jobs with sensible time, memory and cost limits
• Pair with frontend teammates to ship features end to end
• Make production legible with tracing, structured logs, useful errors and fast recovery, and keep an eye on the cloud bill
• Work with AI coding agents every day, and build the guardrails that keep their output trustworthy: tests, specs, types, and the context and skills they need
• Push back on complexity that does not earn its keep

What we are looking for

• 10+ years of professional software development, including production backends
• Strong relational and analytical thinking: schema design, query plans, partitioning, and the failure modes of distributed systems
• Experience with big-data query engines such as Athena, Trino/Presto or DuckDB, and with columnar data formats
• Experience modelling complex domains in code, especially physical ones with units, geometry, capacity and time
• Experience with ontologies or knowledge graphs: modelling entities, relationships and rules that people and machines can both query
• Experience developing or integrating AI and ML models, and the data pipelines and evaluation that make them reliable in production
• Exposure to optimisation, operations research or simulation. You can reason about heuristics, search spaces and trade-offs even if you do not write the solver yourself
• Practical, sceptical fluency with AI tools. You have shipped real work with coding agents and know where they fail
• A test discipline that means deployments rarely surprise you
• A bias toward boring, type-safe technology you can hand off. TypeScript and Python are both welcome

Strong plus

• Hands-on warehouse, logistics or supply-chain experience. You have seen how a real floor runs
• Building LLM-powered features on top of structured data
• Keeping cloud costs under control at scale

What we offer

• Senior ownership of the systems behind a product warehouse managers depend on
• A small senior team where engineers make the engineering decisions
• Hybrid in Cambridge, UK or Tel Aviv, Israel, or fully remote