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Backend Engineer - AI Agent Systems

Digitalwaffle — United Kingdom · Posted ~3 hours ago

Senior Full-time Remote Visa History ✓ £150000-£200000

Skills

Backend engineering AI systems API development Distributed systems Production operations Observability Performance optimization Backend AI APIs Distributed Systems

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Summary ✨ AI‑Generated

Build and operate production-grade backend systems that turn advanced AI capabilities into reliable, fast, observable APIs. You will design systems capable of handling AI workloads at scale, maintain stable integrations with client applications, diagnose production issues, and continuously improve performance and reliability. This is a fully remote UK-based engineering opportunity with a £150k–£200k package.

Highlights

Fully remote UK-based role with a £150k–£200k package, focused on highly reliable AI systems, scalable backend infrastructure, low-latency APIs, observability, and continuous performance and reliability improvements.

Description

We're looking for an experienced AI Engineer to build systems bringing intelligence to everyday organisation and workflows. Our product emphasises high reliability for long‑running tasks, ongoing context, and task execution. As a Backend Engineer, you will design, build, and operate production systems that transform model capabilities into fast, stable, observable APIs used across mobile and desktop clients. Role: Backend Engineer (AI, Agent Systems) Location: UK based remote working Full Time Package £150-£200k Role and responsibilities Creating backend systems which operate reliably at scale, handling AI traffic with low latencyBuilding APIs that are stable, well‑designed, and integrate seamlessly with frontend systemsDetecting production issues, diagnostics, and resolving issues quickly, minimising user impactContinuously improving our product based on real usage, increasing performance and reliability over time Focus Are Backend systems that serve AI‑powered features in productionInference pipelines, orchestration layers, and service boundaries around modelsProduction operations including monitoring, logging, alerting, and incident responsePerformance optimisation across latency, throughput, caching, batching, and streaming Experience Strong backend engineering fundamentals in production environmentsFamiliarity with AI inference patterns (LLMs, embeddings, multimodal systems)Ability to debug distributed systems under loadA bias toward shipping, learning, and iterating from real production behaviour Tech Stack: PythonNode.JSPyTorchLLMs (commercial and open‑source)SQL & NoSQLKubernetesDocker If you are interested to find out more, please apply with your CV today