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ai engineer for an AI platform

Job Description

Описание: ASOS.com is an online fashion retailer serving customers around the world. Its platform is used by millions of people.

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 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
Implement secure and 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, including model access, routing, caching, token optimisation and cost-aware usage controls
Support lifecycle and evaluation practices for agent configurations, prompts and AI workflows
Design secure tool-access patterns for agents, 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 reliability patterns for production AI systems, 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 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
Experience using telemetry to improve reliability and performance
Comfortable working in cloud environments
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
Nice to have: Azure AI Foundry, Azure API Management, AgentOps, MLOps, GenAIOps, monitoring, evaluation and feedback loops

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