Top Tech Jobs & Startup Jobs in London

Build and operate developer productivity tools and shared engineering services used across Wise. Own agentic tooling, security, model access, telemetry, evaluations, and an MCP-based engineering knowledge base. Lead AI enablement through workshops and adoption campaigns, improve developer platforms across the software lifecycle, and use research and data to remove common engineering friction. The role also involves technical leadership, production software ownership, code reviews, system design, and cross-team advocacy.

Lead Wise’s Verification Platform engineering team, managing and mentoring engineers while owning the technical roadmap, architecture, reliability, security, scalability, and operational excellence of business KYC infrastructure. Partner with global product and engineering teams, contribute hands-on when needed, run engineering rituals and incidents, and guide development of configuration-driven rules, review tooling, vendor integrations, distributed decisioning, and event-driven re-evaluation systems.

Leads Wise’s regional marketing strategy across Latin America and MEA, managing Regional Marketing Leads and driving localized acquisition, growth, brand, and performance marketing initiatives. Owns regional budgets, market strategies, customer insights, campaign execution, team development, and cross-functional alignment with central marketing, product, media, creative, PR, and growth teams. Reports performance to senior leadership and builds scalable regional growth playbooks.

Build scalable backend systems and customer-facing financial products for Wise’s shared-finance offerings, including international joint accounts and kid accounts. Collaborate with product, design, data, and research teams to shape ambiguous ideas, influence architecture and product direction, and deliver reliable systems globally. Work includes money movement, spending, authorization, compliance-related systems, shared-account infrastructure, greenfield development, and infrastructure scaling.

Lead Wise’s Risk Modelling ML Engineering pillar for financial crime detection. Own the model lifecycle from experimentation through deployment, monitoring, retraining, drift detection, and auditability. Architect a scalable model factory and experimentation platform supporting hundreds of models under strict latency requirements. Recruit, mentor, and lead senior ML engineers while setting technical standards, making architecture decisions, and partnering with platform teams.

Build Wise’s production ML platform for financial crime detection. Responsibilities include designing declarative training pipelines, model packaging and serving abstractions, evaluation frameworks, monitoring and drift detection, automated retraining, audit trails, and integration with central ML infrastructure. The role focuses on improving data scientist productivity through reliable, scalable, standardized tooling and requires strong software engineering and end-to-end ML lifecycle expertise.

Owns global product compliance strategy for payment processing, customer eligibility, identity verification, regulatory obligation mapping, and multi-licence operations. Translates complex regulatory requirements into scalable product and engineering decisions, partners with legal, product, engineering, and compliance teams, represents compliance positions to regulators and auditors, and strengthens assurance frameworks across Wise’s markets and payment schemes.

Lead the global Receive product domain, setting strategy, executing growth initiatives, and scaling the organization across six teams. Expand offerings internationally, improve onboarding and adoption, optimize pricing and economics, manage financial crime risk, and refine market positioning. Lead and develop product managers, establish team goals and metrics, launch products with go-to-market teams, and remain hands-on in product delivery.

Design, develop, and maintain scalable Java and Spring Boot microservices supporting Wise’s global payment network. Lead event-driven architecture using Kafka, optimize PostgreSQL databases, apply domain-driven design, and collaborate on partner integrations. The role includes code reviews, technical leadership, mentoring junior engineers, and cross-functional work with product, implementation, solutions engineering, and business development teams.

Lead Wise’s Enterprise Risk Analytics strategy, roadmap, and team. Build standardized risk metrics, governance, reporting, data pipelines, monitoring, and audit-ready measurement frameworks. Partner with Data and Engineering to establish reliable models and lineage, quantify risk and business trade-offs, and drive insight-to-action decisions across financial, financial crime, operations, resilience, and regulatory stakeholders. The role also requires strong first- and second-line governance leadership in a regulated fintech environment.