Senior AI Engineer (AI Platform)

Overview

As a Senior AI Engineer, you will contribute to the Agentic AI Platform at ASOS, shaping shared AI foundations and secure enterprise patterns on Azure. You will work with cross-functional teams to enable scalable AI capabilities, from LLMOps to agent lifecycle practices, ensuring observability, reliability and governance by default. This hands-on role focuses on platform design rather than individual use cases, empowering engineering teams to deploy safe, reusable AI components at scale. You will join a mission to accelerate enterprise AI adoption while maintaining risk-aware, performant systems.

Pay / Benefits

• employee discount
• employee sample sales
• 25 days paid annual leave + 1 extra day
• discretionary bonus
• private medical care
• flexible benefits allowance

Responsibilities

• Design and build shared AI platform capabilities on Azure with agentic AI patterns
• Contribute to the Agentic AI Platform initiative and define how agents are built, integrated and operated
• Create standardised templates, reusable components and reference implementations for LLM and Generative AI workflows
• Develop reusable patterns for prompt design, tool calling, multi-step agent flows, retries and failure handling
• Establish engineering standards and best practices for production AI development
• Implement secure, governed access patterns for LLMs and enterprise tools using APIM, gateways, Entra ID, RBAC
• Contribute to LLMOps and model runtime patterns including routing, caching, token optimisation and cost controls
• Support lifecycle and evaluation practices for agent configurations, prompts and AI workflows
• Design secure tool-access patterns for agents and enterprise API integration
• Contribute to AgentOps and GenAIOps capabilities with telemetry, run history and error analysis
• Contribute to reliability patterns for production AI systems including latency, scaling and readiness
• Apply CI/CD and software engineering best practices to AI platform components
• Embed observability by default with logs, metrics and traces
• Collaborate with Cloud Infrastructure and Security to design secure, scalable Azure environments
• Enable cross-team adoption of the platform to move AI from experimentation to production

Key requirements

• Significant experience as an AI Engineer or similar, delivering production-grade AI systems
• Hands-on experience with LLMs, Generative AI and agent-based systems in production
• Experience building reusable AI capabilities or platforms for other teams
• Strong understanding of end-to-end AI lifecycle from experimentation to deployment
• Practical knowledge of production LLM/GenAI runtime concerns (model access, routing, caching, token usage, cost optimization, reliability)
• High proficiency in Python with API and service-oriented development
• Experience with CI/CD, automated testing and versioned deployments for AI components
• Experience with observability tooling (logging, metrics, tracing, alerting) and telemetry-driven reliability
• Hands-on experience with Azure cloud and AI services; Azure AI Foundry preferred, or equivalent
• Experience with Azure API Management (APIM) preferred
• Familiarity with AgentOps, MLOps or GenAIOps concepts including monitoring and feedback loops
• Track record of contributing to engineering standards and reusable patterns for AI
• Strong collaboration skills and ability to influence platform standards

• collaboration
• influence
• pragmatic engineering mindset
• Python
• Azure cloud and AI services
• LLMs / Generative AI

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