As a Senior AI Engineer, you’ll help build and scale AI‑driven solutions that power personalised experiences for millions of ASOS customers. This role focuses on designing reliable, responsible and high‑performing AI systems, using technologies such as large language models (LLMs), generative AI and modern data pipelines.

You’ll work closely with Applied Scientists, Machine Learning Engineers and Product partners to improve how AI systems are developed and delivered. By contributing shared patterns, tooling and infrastructure, you’ll help teams experiment safely, learn quickly and deliver meaningful impact.

What you’ll be doing

Designing and developing AI solutions using LLMs and generative AI, including iterating on prompts and workflows to improve output quality
Building and maintaining scalable data pipelines, applying best practices in data preparation to ensure quality and reliability
Helping to standardise and reuse AI workflows, making it easier for teams across different domains to build consistently and efficiently
Applying MLOps principles to AI systems, including CI/CD, monitoring, model management and feature governance
Partnering with Cloud Infrastructure teams to design secure, cost‑effective environments for AI workloads
Embedding ethical and responsible AI practices into development, proactively identifying and mitigating bias and risk
Fine‑tuning pre‑trained models for specific use cases to improve relevance and performance
Designing and contributing to evaluation frameworks for AI models, including automated testing and benchmarking to support ongoing improvement

About You

Professional experience as an AI Engineer or similar role, with strong exposure to LLMs and generative AI.
Understanding of the end-to-end AI lifecycle, from experimentation through deployment and monitoring.
Proficiency in Python and familiarity with ML/AI libraries (e.g., PyTorch, TensorFlow, Hugging Face).
Experience with prompt engineering and optimisation for generative AI systems.
Comfortable working with cloud platforms (preferably Azure) and containerisation (Docker/Kubernetes).
Knowledge of MLOps tools and practices such as MLflow, CI/CD pipelines, and model monitoring.
Passionate about ethical AI, bias mitigation, and improving developer experience through automation and tooling.
Experience in fine-tuning large language models and adapting them for specific use cases.
Strong understanding of evaluation methodologies for AI systems, including quantitative and qualitative metrics.
Ability to design automated evaluation pipelines for continuous monitoring and improvement of AI models.

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