Senior AI Engineer (AI Platform)

ASOS.com; Greater London; Hybrid; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Employee discount

25 days annual leave

Discretionary bonus scheme

Private medical care

Flexible benefits

Learning opportunities

Job summary

ASOS.com seeks a Senior AI Engineer to join the AI Platform team. You will build shared foundations enabling AI capabilities across ASOS, focusing on agentic AI on Azure and enterprise-scale deployment.

You will partner with Product, Cloud Infrastructure and Security to ensure secure, observable and cost-effective AI platforms while advancing LLMOps and governance. The role emphasizes platform-level work over individual business use cases, with emphasis on standard templates, reference

Qualifications

• Significant experience delivering production-grade AI systems.
• Hands-on work with LLMs, Generative AI and agent-based patterns.
• Strong end-to-end AI lifecycle understanding from experiment to deployment.
• Production readiness: model access, routing, caching, cost optimisation, reliability.
• Proficiency in Python, APIs and service-oriented architectures.
• Experience with CI/CD pipelines and automated testing.
• Familiarity with observability tooling and telemetry for reliability.
• Experience with Azure and related AI tooling is preferred.

Responsibilities

• Design and build AI platform capabilities on Azure focused on agentic AI patterns.
• Define how agents are built, integrated and operated across the organisation.
• Create standard templates and references for LLM/GenAI workflows and tool calling.
• Implement secure access patterns for LLMs and enterprise tools using APIM and RBAC.
• Contribute to MLOps/GenAIOps concepts, including telemetry and feedback loops.
• Ensure reliability through latency monitoring, scaling and observability.
• Embed CI/CD and software engineering best practices for AI platforms.
• Collaborate with Cloud Infrastructure and Security to design secure environments.

Skills

Python

LLMs

Agent-based systems

CI/CD

Observability

Azure

APIM

GenAI platforms

Tools

Azure

APIM

Azure AI Foundry

Job description

We’re ASOS, the online retailer for fashion lovers all around the world.

We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions.

Everyone needs some help showing up as their best self. We’re Disability Confident Committed - let our Talent team know if you need any reasonable adjustments throughout the recruitment process

Job Description

As a Senior AI Engineer, you will be part of the AI Platform team, helping to build and scale the shared foundations that enable AI capabilities across ASOS. The primary focus of this role will be contributing to the Agentic AI Platform initiative, alongside other core AI platform capabilities as the platform evolves.

This role is focused on the platform layer, rather than individual business use cases. You will design and implement shared standards, templates and reference implementations for agentic AI on Azure, enabling application teams to safely design, deploy and operate AI agents at enterprise scale. Working closely with Product teams, Cloud Infrastructure, Security and partners, you will help ensure AI capabilities are secure, observable, reusable and governed by default. You will also contribute to the production foundations needed to operate AI capabilities reliably, including LLMOps, model access patterns, prompt and agent lifecycle practices, observability and secure enterprise integration.

What you’ll be doing

• Designing and building AI platform capabilities on Azure, with a strong focus on agentic AI patterns such as agent runtimes, orchestration and tool integration
• Contributing to the Agentic AI Platform initiative, helping define how agents are built, integrated and operated across the organisation
• Designing and maintaining standardised templates and reference implementations for LLM and Generative AI workflows, enabling teams to adopt consistent patterns for prompt design, tool calling, multi‑step agent flows, retries and failure handling
• Implementing secure, governed access patterns for LLMs and enterprise tools using APIM, platform gateways, Entra ID, RBAC and managed identities
• Contributing to LLMOps and model runtime patterns, including standard approaches for model access, routing, caching, token optimisation and cost‑aware usage controls
• Supporting lifecycle and evaluation practices for agent configurations, prompts and AI workflows, including testing, controlled change and release readiness
• Designing secure tool‑access patterns for agents, including MCP/tool abstraction, credential management and enterprise API integration.
• Contributing to AgentOps and GenAIOps capabilities, including telemetry, run history, task outcomes, error analysis and feedback loops
• Contributing to reliability patterns for production AI systems, including latency monitoring, alerting, scaling considerations and operational readiness.
• Applying CI/CD and software engineering best practices to AI platform and agentic components
• Embedding observability by default, ensuring AI systems are measurable, debuggable and auditable through logs, metrics and traces
• Partnering with Cloud Infrastructure and Security teams to design secure, scalable and cost‑effective Azure environments

Qualifications

• 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, such as model access, routing, caching, token usage, cost optimisation and reliability.
• High proficiency in Python, with experience building APIs and service‑oriented systems
• Experience working with CI/CD pipelines, automated testing and versioned deployments for AI or platform components
• Practical experience with observability tooling (logging, metrics, tracing and alerting) and using telemetry to improve reliability and performance
• Comfortable working in cloud environments, preferably Azure
• Experience with Azure AI Foundry is preferred, but we are equally open to candidates with hands‑on experience using comparable GenAI or agent platforms, and a strong understanding of how to apply those patterns within Azure
• Experience with Azure API Management (APIM) is preferred, especially as a governance or integration boundary
• Familiarity with AgentOps, MLOps or GenAIOps concepts, including monitoring, evaluation and feedback loops
• Strong collaboration skills, with the ability to influence platform standards and enable other engineering teams
• A pragmatic, engineering‑led approach to responsible and ethical AI, with a focus on safety, reliability and trust

Additional Information

BeneFITS’

• Employee discount (hello ASOS discount!)
• Employee sample sales
• 25 days paid annual leave + an extra celebration day for a special moment
• Discretionary bonus scheme
• Private medical care scheme
• Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits
• Opportunity for personalised learning and in‑the‑moment experiences that enable you to thrive and excel in your role