Senior AI / LLM Engineer

asos.com Ltd; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Benefits offered by this job

Employee sample sales

25 days paid annual leave + an extra

Discretionary bonus scheme

Private medical care scheme

Flexible benefits allowance - cash or…

Personalised learning opportunities

Job summary

ASOS is hiring a Senior AI / LLM Engineer to design and industrialise core AI capabilities powering ASOS. You’ll build reusable, production-grade AI platforms that scale across the business, solving deep technical problems in models, reasoning systems, and orchestration.

You’ll work on systems at real scale, partnering with Trust & Security to embed AI risk controls and driving horizontal reuse across squads for cost-effective, high-performance AI solutions.

Qualifications

• 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 across modern AI frameworks (e.g. Semantic Kernel, LangChain or equivalents)

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
• 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

Skills

Azure AI

Azure OpenAI

Python

LangChain

Semantic Kernel

AKS

RAG pipelines

LLM architectures

Agent orchestration

AI safety

Tools

Azure ML

Kubernetes

Job description

We'reASOS, the online retailer for fashion lovers all around the world.

We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS,you'refree to be your true self without judgement, and channel your creativity into a platform used by millions.

Everyone needs some help showing up as their best self.We'reDisability Confident Committed - let our Talent team know if you need any reasonable adjustments throughout the recruitment process

Job Description

We’rehiring aSenior AI / LLM Engineerto 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’llwork on systems thatoperateat real scale, supporting experiences used by millions.

This role sits at the centre of our AI differentiation — focused on solvingdeep technical problems(models, reasoning systems, orchestration), not just feature delivery.You’llcreatereusable, production-grade AI platformsthat teams across ASOS canleverage, accelerating how we build and scale intelligent products.

We’relooking for someone whothinks in systems, not features— with strong abstraction capability and a mindset of building once and reusing at scale.You’llbe comfortable operating in ambiguity, working on frontier AI problems, and balancing innovation with the realities of production environments.

Ifyou’remotivated by solving complex challenges and seeing your work adopted across a global platform, this is a high-impact opportunity.

Responsibilities

• Design and buildLLM-powered systems(RAG, fine-tuning, tool use, multi-agent orchestration)
• Developagentic workflowsfor automation, reasoning, and conversational experiences
• Define patterns forautonomous + human-in-the-loop systems
• Build and scale solutions on theAzure 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 implementLLM evaluation frameworks(offline + online)
• ImplementAI safety guardrails(hallucination control, filtering, explainability)
• Partner with Trust & Security to embedAI risk controls by design
• Enablehorizontal reuse across squads— building once, scaling many times
• Optimise systems forperformance, cost, and reliability(token-aware design)
• Champion best practice inAI engineering, governance, and platform thinking
• Support a culture ofinclusive, responsible AI development

Qualifications

• Strong hands-on experience with theAzure AI ecosystem— including Azure OpenAI, Azure AI Studio, and Azure Machine Learning
• Experience building and runningproduction-grade AI systemson cloud infrastructure (APIs, event-driven architectures, scalable compute such as AKS or similar)
• ProficiencyinPython, with experience working across modern AI frameworks (e.g. Semantic Kernel,LangChainor equivalents)

LLM systems and architecture:

• Deep understanding ofLLMs and transformer-based models, including embeddings, tokenisation, and context management
• Experience designing and optimisingLLM-powered systems, including fine-tuning approaches, structured prompting, and model selection trade-offs
• Experience buildingend-to-end RAG pipelines, including retrieval strategies, vector search, and grounding techniques

Agentic systems & orchestration:

• Experience designingagent-based systems, including multi-agent patterns, tool usage, and workflow orchestration
• Understanding ofstate, memory, and event-driven pipelinesin conversational or decisioning systems

Quality, safety & production readiness:

• Experience implementingevaluation frameworksto measure model quality and performance
• Strong understanding ofAI safety, governance, and guardrails(hallucination mitigation, content safety, explainability)
• Experience designingsecure, scalable, and cost-efficient systemsin production environments

Nice to have:

• LLMOps/MLOpsexperience (CI/CD, experiment tracking, observability)
• Performance and cost optimisation (caching, batching, model routing)

Additional Information

• 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