Associate Product Engineer in London

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.

Role Description

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.

Principal Accountabilities

• 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 data flowing through fraud detection systems, taking end-to-end responsibility without reliance on a separate data team.
  • Identify, investigate, and resolve data quality issues directly, working with engineering and platform where changes are needed.
  • Maintain data hygiene processes that ensure fraud controls are operating on reliable, correct inputs.
  • Build and maintain dashboards and reports that track platform health and detection metrics.
• Software Engineering & Frontend Contribution
  • Contribute to mission‑critical backend services supporting fraud detection (Python/FastAPI and Kotlin/Spring).
  • Drive and deliver customer‑facing fraud features on the frontend, working closely with frontend‑focused engineers in the squad and using React/TypeScript where required.
  • Build and maintain integrations with internal fraud platforms and third‑party vendors.
  • Ensure services are observable, reliable, and meet security and auditability standards for financial crime controls.
  • Apply AI‑assisted development practices effectively, maintaining code quality and maintainability.
• Operational Excellence & Security
  • Apply secure coding practices and contribute to fraud‑aware system design.
  • Ensure appropriate logging, monitoring, and auditability for financial crime controls.
  • Assist in incident investigation and contribute to continuous improvement of fraud response and system reliability.

Personal Attributes & Experience

• Strong analytical and problem‑solving mindset with a genuine interest in fraud, risk, and financial crime, with ability to take ownership of problems end‑to‑end and iterate towards effective solutions.
• Comfortable balancing customer experience, risk mitigation, and operational efficiency in a fast‑paced environment.
• Excellent attention to detail.
• Experience with analysing large datasets with SQL and Python to discover complex trends and patterns.
• Familiarity with supervised machine learning concepts including tree‑based learning, evaluation best practices and explainability.
• Strong sense of ownership over data quality – comfortable identifying inconsistencies and resolving them directly.
• Familiar with building microservices (Python/FastAPI, Kotlin/Spring or similar).
• Comfortable designing scalable solutions to big data problems.
• Familiarity with frontend development (React/TypeScript) is a nice to have.
• Familiarity with cloud platforms (Azure preferred) and CI/CD practices.
• Excellent communicator – able to translate findings and proposals to both technical and non‑technical stakeholders.
• Comfortable working in Agile/squad environments and contributing to squad metrics and delivery.
• Familiarity with third‑party fraud or decisioning platforms is a plus, although not mandatory.
• Demonstrable experience with rule tuning, feature engineering, or model performance optimisation is highly desirable.

Working at Allica Bank

At Allica Bank we want to ensure our employees have the right tools and environment in which to succeed in their role and in support of our customers. Our employees are at the heart of everything we do, so our benefits are designed with you in mind:

• Full onboarding support and continued development opportunities
• Options for flexible working
• Regular social activities
• Pension contributions
• Discretionary bonus scheme
• Private health cover
• Life assurance
• Family friendly policies including enhanced Maternity & Paternity leave