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
