Engineering Lead FinTech AI

ASOS is an online fashion retailer serving customers around the world. Its platform is used by millions.

• Line-manage, develop, hire, and onboard AI Engineers; set objectives, support career progression, manage performance, and balance workload and capacity
• Coach and mentor engineers through design reviews, pairing, and code reviews, and provide constructive feedback
• Own the team’s technical direction, architecture, reusable patterns, and reference solutions
• Set and uphold engineering standards for code quality, testing, evaluation, peer review, CI/CD, and secure-by-default practices
• Make build-or-buy decisions and monitor running costs, performance, and technical debt
• Write code, prototype, unblock the team, and take on the most challenging builds
• Design, build, and ship production-ready agentic AI and automation solutions that plan, reason, use tools, retrieve information, act across systems, and hand work back to people when appropriate
• Build integrations with platforms including Microsoft Dynamics 365 Finance and Operations, ReconArt, Concur, ServiceNow, and the data platform; use retrieval augmented generation and grounding to ensure accuracy against business data
• Own end-to-end delivery, plan and prioritise the backlog, manage capacity and dependencies, and move work from proof of concept into production
• Run the team’s work through Azure DevOps and follow ASOS delivery processes, including governance, change control, and release cadence
• Support live agents and automations; establish monitoring, alerting, runbooks, and clear ownership, and lead incident response
• Work with Finance, Commercial, Buying, and Merchandising teams to understand their processes, identify worthwhile automation, and explain options clearly
• Build within the central AI team’s policies, approved tooling, and guardrails; coordinate with that team and the AI centre of excellence
• Track and evidence benefits, including time saved, manual effort removed, and shorter cycle times; report progress and risks to senior stakeholders

• Experience line-managing engineers, including one-to-ones, development, performance management, and hiring, while remaining technically hands-on
• Track record of setting technical direction and engineering standards and improving team output
• Experience owning team delivery, including planning, prioritisation, capacity management, and reporting to senior stakeholders
• Comfortable delivering within a framework owned by another team, collaborating with a central or platform team, and pushing back constructively when needed
• Demonstrable experience designing and building agentic AI solutions that are live and actively used, not just pilots
• Practical experience with LLM and agent frameworks such as Microsoft Copilot Studio, Azure AI Foundry, Azure OpenAI, Semantic Kernel, LangChain, LangGraph, AutoGen, or CrewAI
• Knowledge of agent patterns including tool calling, orchestration, memory, multi-agent workflows, and retrieval augmented generation
• Experience with workflow and process automation tools such as Power Platform, Logic Apps, or RPA, and evaluating agents for accuracy, guardrails, reliability, and cost
• Strong software or data engineering background, solid coding skills in Python or C#/.NET, and experience building and integrating APIs and services
• Experience deploying and operating cloud solutions, ideally on Azure, with CI/CD, testing, monitoring, and observability; security- and data-conscious when handling sensitive financial data
• Comfortable working with non-technical stakeholders, running discovery, explaining technical ideas simply, and influencing at senior level with an outcome-focused approach
• Будет плюсом: finance systems or processes such as accounts payable, reconciliation, or financial control; Microsoft Dynamics 365 Finance and Operations; retail, ecommerce, or fashion experience, particularly in commercial, buying, merchandising, or supply chain; SQL, data modelling, Databricks, or Microsoft Fabric; responsible AI and governance, Model Context Protocol (MCP), or ITIL-based service management

• Локация: Лондон
• Employee discount and employee sample sales
• 25 Days of paid annual leave plus an extra celebration day
• Discretionary bonus scheme
• Private medical care scheme
• Flexible benefits allowance, available as extra cash or towards other benefits
• Personalised learning and in-the-moment development opportunities