Reference: 50878Senior Python Backend Engineer (AI / LLMs) Remote (United Kingdom) | Permanent | Flexible compensation + equity We're working with a well-established, tech-led business that is building a new AI product focused on handling real-world tasks, workflows and decision-making. This is a small, high-calibre team building systems where AI capability is translated into reliable, structured product behaviour, with a strong emphasis on execution and consistency in real usage.
The product focuses on: Long-running workflowsPersistent contextMulti-step task executionIntegration with external systems The core challenge is designing systems that can apply model capability in a structured and reliable way, even when behaviour is non-deterministic.
The Role This role sits in the backend layer that connects models to the product. The focus is on designing and operating systems that enable: AI workflows to run end-to-endAPIs to serve AI features consistentlySystems to perform reliably under real usage conditions You'll be working on: Inference pipelines and orchestration layersBackend services for AI-driven workflowsPerformance considerations such as latency, throughput, batching and cachingMonitoring, logging and production reliabilityWhat They Care About The hiring bar is centred around real production experience: Whether you have owned backend systems end-to-end in productionYour experience working with AI systems beyond simple integrationYour exposure to practical challenges such as:latency and throughput optimisationmonitoring and observabilitydebugging and incident handlingscaling systems in production environmentsTech EnvironmentPython (primary backend language)Node.jsSQL / NoSQL databasesLLM ecosystem (OpenAI, Anthropic, etc.)Docker and KubernetesAWS, Azure or GCP is fine The emphasis is on how you design and run systems, rather than the specific cloud used.
Team & Working StyleFully remote-first, work from anywhereSmall, highly capable engineering teamStrong emphasis on ownership and deliveryComfortable working in evolving systems and making pragmatic decisions.
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