27 days ago
London, United KingdomSenior
Responsibilities
- Design and build Azure-based AI platform capabilities focused on agent runtimes, orchestration, and tool integration.
- Define the Agentic AI Platform approach for building, integrating, and operating agents across ASOS.
- Create standardized templates and reference implementations for LLM and generative AI workflows.
- Implement secure and governed LLM and enterprise-tool access using API Management, platform gateways, Entra ID, RBAC, and managed identities.
- Contribute to LLMOps, model runtime, AgentOps, and GenAIOps capabilities, including model access, routing, caching, evaluation, telemetry, and feedback loops.
- Design secure tool-access patterns, credential management, enterprise API integrations, and MCP/tool abstractions.
- Develop reliability, observability, monitoring, alerting, scaling, and operational-readiness patterns for production AI systems.
- Partner with Cloud Infrastructure, Security, Product teams, and engineering teams to establish secure, scalable, reusable, and cost-effective standards.
Requirements
- Significant experience as an AI Engineer, AI Platform Engineer, or similar role 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 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 using telemetry to improve reliability and performance.
- Comfort working in cloud environments, preferably Azure.
- Preferred experience with Azure AI Foundry or comparable GenAI and agent platforms.
- Preferred experience with Azure API Management as a governance or integration boundary.
- Familiarity with AgentOps, MLOps, or GenAIOps concepts, including monitoring, evaluation, and feedback loops.
- 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.
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.
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