> Markdown version of [/jobs/ext/2048978-senior-ai-llm-engineer](https://www.wearedevelopers.com/jobs/ext/2048978-senior-ai-llm-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI / LLM Engineer - **Company:** asos.com Ltd - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Cloud Computing, Continuous Integration, Python (Programming Language), Azure Machine Learning, Software Safety, Search Technologies, Tokenization, Workflow Management Systems, Large Language Models, Multi-Agent Systems, Event Driven Architecture, Build Management, AI Platforms, Machine Learning Operations, GPT - **Published:** August 14, 2026 - **Apply:** https://jobs.smartrecruiters.com/ASOS/744000135043984-senior-ai-llm-engineer ## About the Role Tech stack & platform experience (core): * Strong hands-on experience with the Azure AI ecosystem - including Azure OpenAI, Azure AI Studio, and Azure Machine Learning * Experience building and running production-grade AI systems on cloud infrastructure (APIs, event-driven architectures, scalable compute such as AKS or similar) * Proficiency in Python, with experience working across modern AI frameworks (e.g. Semantic Kernel, LangChain or equivalents) LLM systems and architecture: * Deep understanding of LLMs and transformer-based models, including embeddings, tokenisation, and context management * Experience designing and optimising LLM-powered systems, including fine-tuning approaches, structured prompting, and model selection trade-offs * Experience building end-to-end RAG pipelines, including retrieval strategies, vector search, and grounding techniques Agentic systems & orchestration: * Experience designing agent-based systems, including multi-agent patterns, tool usage, and workflow orchestration * Understanding of state, memory, and event-driven pipelines in conversational or decisioning systems Quality, safety & production readiness: * Experience implementing evaluation frameworks to measure model quality and performance * Strong understanding of AI safety, governance, and guardrails (hallucination mitigation, content safety, explainability) * Experience designing secure, scalable, and cost-efficient systems in production environments Nice to have: * LLMOps / MLOps experience (CI/CD, experiment tracking, observability) * Performance and cost optimisation (caching, batching, model routing) ## Description We're hiring a Senior AI / LLM Engineer to design and industrialise the core AI capabilities that will power ASOS. At ASOS, AI is central to how we evolve the customer experience - from product discovery and personalisation through to operational decision-making. You'll work on systems that operate at real scale, supporting experiences used by millions. This role sits at the centre of our AI differentiation - focused on solving deep technical problems (models, reasoning systems, orchestration), not just feature delivery. You'll create reusable, production-grade AI platforms that teams across ASOS can leverage, accelerating how we build and scale intelligent products. We're looking for someone who thinks in systems, not features - with strong abstraction capability and a mindset of building once and reusing at scale. You'll be comfortable operating in ambiguity, working on frontier AI problems, and balancing innovation with the realities of production environments. If you're motivated by solving complex challenges and seeing your work adopted across a global platform, this is a high-impact opportunity. Responsibilities * Design and build LLM-powered systems (RAG, fine-tuning, tool use, multi-agent orchestration) * Develop agentic workflows for automation, reasoning, and conversational experiences * Define patterns for autonomous + human-in-the-loop systems * Build and scale solutions on the Azure AI stack (Azure OpenAI, AI Studio, Azure ML, Cognitive Services) * Create reusable infrastructure: Prompt orchestration layers, Vector search and retrieval pipelines & Evaluation and observability frameworks * Design and implement LLM evaluation frameworks (offline + online) * Implement AI safety guardrails (hallucination control, filtering, explainability) * Partner with Trust & Security to embed AI risk controls by design * Build reusable AI capabilities (e.g. stylist reasoning, product understanding, copilots) * Enable horizontal reuse across squads - building once, scaling many times * Optimise systems for performance, cost, and reliability (token-aware design) * Champion best practice in AI engineering, governance, and platform thinking * Support a culture of inclusive, responsible AI development ## Related Videos - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [This App Reached 10,000 Users in One Week. Here's How.](https://www.wearedevelopers.com/videos/100329-this-app-reached-10-000-users-in-one-week-here-s-how) - [When Value Becomes Programmable: A Developer's Guide to Tokenization](https://www.wearedevelopers.com/videos/100276-when-value-becomes-programmable-a-developer-s-guide-to-tokenization) - [From AI Assistance to Agentic Systems: Scaling Sovereign AI in Banking](https://www.wearedevelopers.com/videos/100070-from-ai-assistance-to-agentic-systems-scaling-sovereign-ai-in-banking) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)