Senior AI / LLM Engineer

Description

The company is hiring a senior engineer to design and industrialise its core AI capabilities, which will underpin the company platform.

AI shapes how the company improves the customer experience, from product discovery and personalisation to operational decisions. The systems you build run at real scale and serve millions of people.

The role focuses on hard technical problems across models, reasoning systems and orchestration rather than only shipping features. You will build production-grade AI platforms that teams across the company can reuse, which speeds up how intelligent products are built and scaled.

The ideal candidate reasons in terms of systems, designs for abstraction, and aims to build once and reuse widely. You will be comfortable with ambiguity, work on cutting-edge AI problems, and balance experimentation with the demands of production.

This suits someone who enjoys complex challenges and wants their work adopted across a global platform.

Responsibilities

• Build LLM-based systems using retrieval-augmented generation, fine-tuning, tool use and multi-agent orchestration.
• Create agentic workflows for automation, reasoning and conversational products.
• Set patterns for systems that mix autonomous behaviour with human-in-the-loop review.
• Build and scale solutions on the Azure AI stack, including Azure OpenAI, AI Studio, Azure ML and Cognitive Services.
• Develop shared infrastructure: prompt orchestration layers, vector search and retrieval pipelines, and evaluation and observability frameworks.
• Design and implement LLM evaluation frameworks covering both offline and online testing.
• Add AI safety guardrails for hallucination control, filtering and explainability.
• Work with Trust and Security to build AI risk controls into designs from the start.
• Build reusable AI capabilities such as stylist reasoning, product understanding and copilots.
• Make capabilities reusable across squads so each is built once and used many times.
• Optimise performance, cost and reliability, designing with token use in mind.
• Promote good practice in AI engineering, governance and platform design.
• Help sustain responsible, inclusive AI development.

Requirements

• Hands-on experience with the Azure AI ecosystem, including Azure OpenAI, Azure AI Studio and Azure Machine Learning.
• Experience building and running production AI systems on cloud infrastructure, such as APIs, event-driven architectures and scalable compute like AKS or similar.
• Proficiency in Python and experience with modern AI frameworks such as Semantic Kernel, LangChain or equivalents.
• A deep understanding of LLMs and transformer models, including embeddings, tokenisation and context management.
• Experience designing and tuning LLM-powered systems, covering fine-tuning, structured prompting and trade-offs in model selection.
• Experience building end-to-end RAG pipelines, including retrieval strategies, vector search and grounding.
• Experience designing agent-based systems with multi-agent patterns, tool use and workflow orchestration.
• An understanding of state, memory and event-driven pipelines in conversational or decisioning systems.
• Experience implementing evaluation frameworks that measure model quality and performance.
• A strong grasp of AI safety, governance and guardrails, including hallucination mitigation, content safety and explainability.
• Experience designing secure, scalable and cost-efficient systems in production.
• LLMOps or MLOps experience, including CI/CD, experiment tracking and observability.
• Experience with performance and cost optimisation, such as caching, batching and model routing.
• Additional information is provided in the posting.

Conditions

The company is an online fashion retailer serving customers worldwide.

Reasonable adjustments are available throughout recruitment; tell the Talent team if you need one.

The company is a Disability Confident Committed employer.

Benefits

• Employee discount.
• Access to employee sample sales.
• 25 days of paid annual leave, plus an extra day to celebrate a special moment.
• A discretionary bonus scheme.
• Private medical care.
• A flexible benefits allowance that you can take as extra cash or spend on other benefits.
• Personalised learning and in-the-moment development opportunities to help you grow in the role.