ai engineer for an AI platform

ASOS.com is an online fashion retailer serving customers around the world. Its platform is used by millions of people.

• Design and build AI platform capabilities on Azure, focusing on agentic AI patterns such as agent runtimes, orchestration and tool integration;
• Contribute to the Agentic AI Platform initiative and define how agents are built, integrated and operated across the organisation;
• Design and maintain standardised templates and reference implementations for LLM and Generative AI workflows;
• Implement secure and governed access patterns for LLMs and enterprise tools using APIM, platform gateways, Entra ID, RBAC and managed identities;
• Contribute to LLMOps and model runtime patterns, including model access, routing, caching, token optimisation and cost-aware usage controls;
• Support lifecycle and evaluation practices for agent configurations, prompts and AI workflows;
• Design secure tool-access patterns for agents, including MCP/tool abstraction, credential management and enterprise API integration;
• Contribute to AgentOps and GenAIOps capabilities, including telemetry, run history, task outcomes, error analysis and feedback loops;
• Contribute to reliability patterns for production AI systems, including latency monitoring, alerting, scaling considerations and operational readiness;
• Apply CI/CD and software engineering best practices to AI platform and agentic components;
• Embed observability through logs, metrics and traces;
• Partner with Cloud Infrastructure and Security teams to design secure, scalable and cost-effective Azure environments.

• Significant experience as an AI Engineer, AI Platform Engineer or similar, delivering production-grade AI systems;
• Hands-on experience with LLMs, Generative AI and agent-based systems in real-world environments;
• Strong understanding of the end-to-end AI lifecycle, from experimentation through deployment and operation;
• Practical understanding of production LLM or GenAI runtime concerns, including model access, routing, caching, token usage, cost optimisation and reliability;
• High proficiency in Python and experience building APIs and service-oriented systems;
• Experience with CI/CD pipelines, automated testing and versioned deployments for AI or platform components;
• Practical experience with observability tooling, including logging, metrics, tracing and alerting;
• Experience using telemetry to improve reliability and performance;
• Comfortable working in cloud environments;
• Strong collaboration skills and the ability to influence platform standards and enable other engineering teams;
• Pragmatic, engineering-led approach to responsible and ethical AI, focused on safety, reliability and trust;
• Nice to have: Azure AI Foundry, Azure API Management, AgentOps, MLOps, GenAIOps, monitoring, evaluation and feedback loops.

• Employee discount;
• Employee sample sales;
• 25 Days paid annual leave plus an extra celebration day;
• Discretionary bonus scheme;
• Private medical care scheme;
• Flexible benefits allowance, available as extra cash or for other benefits;
• Personalised learning and in-the-moment development opportunities.