Senior AI Engineer (AI Platform)

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

• 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

• 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

• 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