Senior Engineering Lead (FinTech AI)

Company 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.

But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list.

Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you.

Job Description

We’re looking for a Senior Engineering Lead to build and lead our AI engineering team in FinTech and Fashion Tech at ASOS, the technology teams behind Finance and our Commercial, Buying and Merchandising functions. This is a hands on engineering leadership role. You’ll line manage and grow a team of AI Engineers who build, deploy and support automation and agentic AI solutions, and you’ll still write code yourself when it counts.

The teams we support run some of the highest volume, most process heavy operations in the business, from accounts payable, reconciliation and expenses in Finance, through to range planning, trading, stock and supplier data on the commercial side. There is real scope to take repetitive manual work off people, speed up decisions and give them their time back.

This is a delivery role rather than a strategy one. ASOS has a central AI team who own our AI policy, framework, approved tooling and guardrails, and you won’t be setting that direction for the wider business. You’ll build for the teams we support within it, working closely with the central team and our AI centre of excellence to stay aligned. Within that remit you own delivery end to end, from understanding the problem through to supporting what goes live, including the agents already running today.

Key Responsibilities

Leading and Growing the Engineering Team

• Line manage a team of AI Engineers, covering objectives, one to ones, development, career progression and performance.

• Grow the team. Hire well, onboard new engineers properly, and build the skills we need as the work changes.

• Coach and mentor through design reviews, pairing and code review, and give honest feedback that helps people improve.

• Look after the health of the team, balancing workload and capacity so people are on the right work and not carrying too much.

Technical Direction and Engineering Standards

• Own the technical direction for the team, including the architecture, reusable patterns and reference solutions we build from.

• Set and hold the engineering standards, covering code quality, testing, evaluation, peer review, CI/CD and secure by default habits.

• Make the build or buy calls for your team, and keep an eye on running cost, performance and technical debt.

Building and Running AI Solutions

• Stay hands on. Lead from the front by writing code, prototyping, unblocking your team and picking up the hardest builds yourself.

• Design, build and ship production ready agentic AI and automation solutions: agents that can plan, reason, use tools, retrieve information, act across our systems and hand back to a person when they should.

• Build the integrations that make agents genuinely useful, connecting them to platforms such as Microsoft Dynamics 365 Finance and Operations, ReconArt, Concur, ServiceNow and our data platform, and use retrieval augmented generation and grounding so solutions are accurate against real business data.

Owning Delivery

• Own delivery for the team. Plan and prioritise the backlog, manage capacity and dependencies, and move work quickly from proof of concept into production.

• Run the team’s work through Azure DevOps and follow the wider ASOS delivery process, including governance, change control and release cadence.

• Own the agents and automations already live, put proper operational foundations in place including monitoring, alerting, runbooks and clear ownership, and lead incident response when things go wrong.

Working with Stakeholders and the Central AI Team

• Get out into Finance, Commercial, Buying and Merchandising to understand how people really work and what is genuinely worth automating, and explain the options back in plain language.

• Build inside the policies, approved tooling and guardrails the central AI team sets, and be our main point of contact with them and the AI centre of excellence so we stay aligned.

• Track and evidence the benefit delivered, whether that is time saved, manual effort removed or cycle times cut, and report progress and risks honestly to senior stakeholders.

Why This Role Matters

Automation and agentic AI are the biggest opportunity we have to change how these teams work. Done well, they take repetitive work off people’s plates, shorten month end close and trading decisions, and free our teams up for the things only people can do.

The central team provides the framework and the guardrails. What we need now is someone to build and lead the team that delivers against it: a hands on engineering leader who can grow engineers, set the technical bar, keep stakeholders confident, and still open the laptop and build.

Qualifications

Engineering Leadership

• Experience line managing a team of engineers, covering one to ones, development, performance and hiring, while staying technically hands on.

• A track record of setting technical direction and engineering standards, and lifting the quality of what a team produces.

• Experience owning delivery for a team, including planning, prioritisation, capacity and reporting progress to senior stakeholders.

• Comfortable delivering inside a framework someone else owns, working alongside a central or platform team, and able to push back constructively when it matters.

AI and Automation

• Real, demonstrable experience designing and building agentic AI solutions that have gone live and are genuinely used, rather than pilots.

• Strong practical experience with LLM and agent frameworks such as Microsoft Copilot Studio, Azure AI Foundry, Azure OpenAI, Semantic Kernel, LangChain, LangGraph, AutoGen or CrewAI, and with core agent patterns including tool calling, orchestration, memory, multi agent workflows and retrieval augmented generation.

• Experience with workflow and process automation tooling such as Power Platform, Logic Apps or RPA, and with evaluating how agents perform across accuracy, guardrails, reliability and cost.

Engineering and Communication

• A strong software or data engineering background, with solid coding skills such as Python or C#/.NET, and experience building and integrating APIs and services.

• Experience deploying and running solutions in the cloud, ideally Azure, with proper CI/CD, testing, monitoring and observability, and a security and data conscious mindset when working with sensitive financial data.

• Genuinely comfortable with non technical stakeholders, able to run discovery, explain technical ideas simply and influence at senior level, with a focus on outcomes rather than technology for its own sake.

We’d Also Love to See

• Experience with finance systems or processes such as accounts payable, reconciliation or financial control, or with Microsoft Dynamics 365 Finance and Operations.

• Experience in retail, ecommerce or fashion, particularly across commercial, buying, merchandising or supply chain.

• Data skills including SQL, data modelling and platforms such as Databricks or Microsoft Fabric.

• Experience with responsible AI and governance, emerging agent standards such as Model Context Protocol (MCP), or ITIL based service management.

Why You’ll Love This Role

• You will build and lead the AI engineering capability for two of the most important areas of ASOS, and shape how the team works from the ground up.

• It is a rare mix. You get to line manage and grow a team, own the technical direction, and still build.

• Real problems, real scale and real users, with a clear impact on people’s working lives.

• A central AI team owns the framework, tooling and guardrails, so you can concentrate on building and leading rather than writing policy.

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