6 hours ago
London, United KingdomSenior
Responsibilities
- Design and build shared AI platform capabilities on Azure, with emphasis on agent runtimes, orchestration, and tool integration.
- Contribute to the Agentic AI Platform initiative and define how agents are built, integrated, and operated across the organization.
- Create standardized templates and reference implementations for LLM and Generative AI workflows.
- Implement secure and governed access patterns for LLMs and enterprise tools using APIM, Entra ID, RBAC, and managed identities.
- Develop LLMOps, AgentOps, and GenAIOps capabilities covering model access, routing, caching, token optimization, telemetry, evaluation, and feedback loops.
- Design secure tool-access patterns, credential management approaches, and enterprise API integrations.
- Contribute to production reliability through latency monitoring, alerting, scaling, operational readiness, and embedded observability.
- Apply software engineering, automated testing, versioned deployment, and CI/CD practices to AI platform components.
- Partner with Cloud Infrastructure, Security, Product teams, and external partners to create secure, scalable, and cost-effective Azure environments.
Requirements
- 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 AI lifecycle from experimentation through deployment and operation.
- Practical knowledge of production LLM or GenAI runtime concerns, including model access, routing, caching, token usage, cost optimization, 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 and telemetry for improving reliability and performance.
- Comfort working in cloud environments, preferably Azure.
- Experience with Azure AI Foundry is preferred, or comparable GenAI or agent platforms with a strong understanding of applying those patterns within Azure.
- Experience with Azure API Management, particularly as a governance or integration boundary, is preferred.
- Familiarity with AgentOps, MLOps, or GenAIOps concepts, including monitoring, evaluation, and feedback loops.
- Strong collaboration and influencing skills, with a pragmatic engineering-led approach to responsible and ethical AI.
Benefits
- Employee discount and access to employee sample sales.
- 25 days of paid annual leave plus an additional celebration day.
- Discretionary bonus scheme.
- Private medical care scheme.
- Flexible benefits allowance that can be taken as cash or used toward other benefits.
- Personalized learning and in-the-moment development experiences.
- ASOS is Disability Confident Committed and supports reasonable adjustments during recruitment.
Categories
About ASOS
ASOS is a global online fashion and beauty retailer for 20‑somethings, selling own‑brand and third‑party labels via its website and mobile apps. The company earns revenue from direct‑to‑consumer e‑commerce, shipping to customers worldwide and offering marketplace services for brands. Founded in 2000 and headquartered in London, ASOS is a public company listed on the London Stock Exchange and runs in‑house content and fulfillment operations at scale.