Senior Engineering Manager (.NET) in London

You might not know our name, but companies like e Bay, Spotify, Klarna, Uber, and Sony do, because we're behind many of the digital experiences you use every day.

Whether you want to book a holiday, order food, renew a subscription, or check out online, there's a good chance our tech powers the payments behind the scenes.

Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. com is looking for an ambitious Senior Engineering Manager to join our Disputes team.

Our mission is to build the tools, services, and models that help merchants manage and win disputes at scale - reducing the cost and operational burden of chargebacks while protecting revenue for our merchants and our business.

Disputes sit at the intersection of merchant-facing products, complex scheme and regulatory processes, and data-driven decisioning.

Our team owns the full stack, anchored by a .

NET back end that manages the dispute lifecycle and integrates with card schemes, alongside the front-end experiences merchants use to track and respond to disputes and the machine learning models that predict outcomes and recommend the best action on every case.

We're building for scale, and that scale brings ambiguity, shifting priorities, and the occasional setback - so we're looking for a resilient leader who has built and sustained high-performing teams, learned from failure, and come back stronger.

Above all, you'll be someone who drives predictable delivery and operational efficiency: shipping consistently, running systems reliably, and continuously improving how the team works.

NET back end, with front-end and machine learning components, helping engineers establish and validate their understanding of technical architecture and design end-user-centric systems and tools.

Own predictable, high-velocity delivery — establishing healthy engineering practices, sensible estimation, and a smooth path from idea to production so the team ships consistently and sustainably.

Drive operational efficiency and reliability by automating processes — including monitoring and alerting — meeting SLAs/SLOs, reducing operational cost, and minimising toil to keep the team focused on high-value work rather t Continuously improve delivery and operational metrics (e. g. cycle time, deployment frequency, change failure rate, and incident response), using data to identify bottlenecks and raises the bar over time.

Cultivate an inclusive environment where every team member feels they belong, and mentors them in both their career development and interpersonal skills.

Collaborate across Engineering, Product, and Operations to deliver solutions for merchant and internal dispute use cases.

Operating in a highly regulated financial space, ensure compliance with a range of control frameworks — from internal stakeholders such as Info Sec and Internal Audit, to external auditors, card schemes, and regulators.

Oversee the responsible use of machine learning and AI in dispute decisioning, leading the team to develop the infrastructure, tooling, and governance required to run models safely and at scale in production.

You're energised by a high-growth environment, comfortable making decisions with imperfect information, and you keep the team moving and shipping when priorities shift under you.

Proven experience building, growing, and sustaining high-performing engineering teams over time — not just standing them up.

A strong back-end engineering background, ideally in .

NET / C#, leading teams building scalable, event-driven services and APIs.

Comfortable also overseeing front-end and machine learning work, able to earn credibility and make sound trade-offs across disciplines even where you aren't the deepest expert.

NET / C#, REST APIs, event-driven and microservice architectures.

Front end: React, Type Script.

Machine learning: Python, model training and serving, and the infrastructure to run models in production.

Data & platform: SQL, plus experience designing batch and stream data-processing systems. AWS and/or GCP, Docker, Terraform, and observability tooling such as Datadog.

Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.