AI Engineer (AI Platform)

Описание

ASOS is an online fashion retailer serving customers around the world.

Задачи

• 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 help 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, including prompt design, tool calling, multi-step agent flows, retries and failure handling




• Implement secure, 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 for model access, routing, caching, token optimisation and cost-aware usage controls




• Support lifecycle and evaluation practices for agent configurations, prompts and AI workflows, including testing, controlled change and release readiness




• Design secure agent tool-access patterns, 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 production AI reliability patterns, 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 by default so AI systems are measurable, debuggable and auditable through logs, metrics and traces




• Partner with Cloud Infrastructure and Security teams to design secure, scalable and cost-effective Azure environments

Требования

• 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, and using telemetry to improve reliability and performance




• Comfortable working in cloud environments




• Strong collaboration skills and ability to influence platform standards and enable other engineering teams




• Take a pragmatic, engineering-led approach to responsible and ethical AI, focusing on safety, reliability and trust Будет плюсом: Azure AI Foundry or comparable GenAI or agent platforms, Azure API Management (APIM), AgentOps, MLOps or GenAIOps concepts, including monitoring, evaluation and feedback loops

Условия

• 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 towards other benefits




• Personalised learning and in-the-moment development opportunities