Associate Product Engineer

About Allica Bank

Allica is the UK’s fastest growing company - and the fastest-growing financial technology (Fintech) firm ever. Our purpose is to help established SMEs, one of the last major underserved opportunities in Fintech.

Established SMEs are the backbone of local communities - representing over a third of our economy - yet have been largely neglected both by traditional high street banks and modern fintech providers.

This role sits within the Payments Tribe, which has built Allica’s current account for established SMEs, combining modern technology with a best-in-class customer experience.

The tribe is responsible for payments, current accounts, and savings propositions, and plays a critical role in enabling secure and seamless financial operations for our customers. Technology sits at the centre of Allica. We design and build the platforms that power the bank, working closely with Product, Risk, Compliance, and Operations to deliver meaningful outcomes.

Our teams move quickly, take ownership end-to-end, and operate without the burden of legacy systems. Within this context, Financial Crime is a critical and fast‑evolving problem space. We are building modern, data‑driven fraud capabilities to protect our customers and the bank, increasingly leveraging machine learning and AI techniques alongside traditional controls to stay ahead of evolving threats.

We are looking for an Associate Product Engineer to join our Fraud squad. This is an entry-to-mid level role suited to someone with a strong foundation in data and a genuine interest in machine learning and financial crime, who is eager to develop hands‑on expertise in fraud detection and prevention. Reporting to the Product Engineer for Fraud, you will work closely within a small, focused squad contributing to the full lifecycle of fraud controls – from identifying a problem through to shipping a solution.

Your primary focus will be on fraud rule management, data quality and integrity across fraud platforms, and applying ML and data‑driven thinking to emerging fraud problems. You will also have the opportunity to take end‑to‑end product ownership of specific fraud areas, and to contribute to customer‑facing fraud features alongside the squad. This is an ideal role for someone who is analytically strong, curious about fraud and financial crime, and wants to grow into a more senior product engineering position over time.

• Product Ownership within the Fraud Domain

  Take end‑to‑end ownership of specific fraud problem areas – from discovery and definition through to delivery, iteration, and ongoing performance monitoring.

  Translate fraud risks, customer needs, and operational challenges into clearly scoped, deliverable solutions.

  Work closely with Risk, Compliance, and Operations to understand the control landscape and prioritise the right problems to solve.

  Contribute to squad planning, backlog refinement, and delivery ceremonies, bringing both product thinking and technical judgement.

• Fraud Control Optimisation and Threat Analysis

  Build AI-native tools (using SQL & Python) for analysing the performance of our rule‑based and machine learning controls, to reduce false positives and improve recall.

  Support the ongoing tuning and optimisation of fraud controls across Allica’s platforms. Work with operational and compliance teams to translate investigative findings into actionable improvements.

  Document change rationale and expected performance outcomes clearly and accurately.

  Stay informed on emerging ML/AI techniques relevant to fraud (anomaly detection, behavioural analytics, generative AI risks such as deepfakes and synthetic identities).

  Propose and prototype new detection rules or signals to address emerging fraud typologies (APP fraud, account takeover, synthetic identities).

  Support A/B testing and evaluation of new controls.

  Develop working familiarity with machine learning concepts and their application in the fraud domain.

  Proactively monitor fraud intelligence sources and internal data to identify new or evolving threat patterns.

• Data Quality & Integrity in Fraud Platforms

  Own the accuracy and completeness of…