Senior AI LLM Engineer

Were 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. Youll 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. Youll create reusable production-grade AI platforms that teams across ASOS can leverage accelerating how we build and scale intelligent products. 

Were looking for someone who thinks in systems not features  with strong abstraction capability and a mindset of building once and reusing at scale. Youll be comfortable operating in ambiguity working on frontier AI problems and balancing innovation with the realities of production environments. 

If youre 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 

Qualifications :

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) 

Additional Information :

BeneFITS 

• Employee discount (hello ASOS discount!) 
• Employee sample sales 
• 25 days paid annual leave an extra celebration day for a special moment 
• Discretionary bonus scheme 
• Private medical care scheme 
• Flexible benefits allowance - which you can choose to take as extra cash or use towards other benefits 
• Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role 

Remote Work :

No

Employment Type :

Full-time