Associate Product Engineer

Job not on LinkedIn

🕒 Yesterday

🏢🏡 London – Hybrid

⏰ Full Time

🟢 Junior

🟡 Mid-level

🧑‍💻 Full-stack Engineer

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BVNK

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2022

💳 Fintech

💸 Finance

₿ Crypto

💰 Series A on 2022-05

Fintech • Finance • Crypto

BVNK is a company that provides enterprise-grade payments infrastructure specifically designed for stablecoins. Their platform facilitates the seamless movement of money across global networks by enabling businesses to send, receive, store, and convert fiat and stablecoins at high speeds. BVNK's offerings include compliance with international regulatory standards, robust security measures, and flexible integration options for payment service providers and financial institutions. They cater to businesses in various industries, including CFD and forex, iGaming, and digital asset management, by offering solutions like virtual accounts and stablecoin wallets. Their mission is to bridge banks and blockchains, accelerating global money movement while ensuring regulatory compliance and operational efficiency.

📋 Description

• 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. • 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 (e.g. 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 (e.g. 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. • 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. • 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 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.

🎯 Requirements

• Strong analytical and problem-solving mindset with a genuine interest in fraud, risk, and financial crime • 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

🏖️ Benefits

• 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